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Генеративные модели в машинном обучении (ИИ 2025) - История изменений
2026-09-28T02:53:08Z
История изменений этой страницы в вики
MediaWiki 1.43.9
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94064&oldid=prev
Mkgoldshteyn в 15:13, 5 декабря 2025
2025-12-05T15:13:07Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:13, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l87">Строка 87:</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''8''' || Амортизированный вариационный вывод, трюк репараметризации, VAE, ELBO Surgery, Learnable Prior|| [https://m.vkvideo.ru/video-227011779_456239552?t=1h9m44s Лекция VK] [https://m.vkvideo.ru/video-227011779_456239554?t=19m46s Семинар VK] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec4_vae.pdf Лекция] [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/seminars/pro/sem4_vae.ipynb Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''8''' || Амортизированный вариационный вывод, трюк репараметризации, VAE, ELBO Surgery, Learnable Prior|| [https://m.vkvideo.ru/video-227011779_456239552?t=1h9m44s Лекция VK] [https://m.vkvideo.ru/video-227011779_456239554?t=19m46s Семинар VK] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec4_vae.pdf Лекция] [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/seminars/pro/sem4_vae.ipynb Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK<ins style="font-weight: bold; text-decoration: none;">] [https://www.youtube.com/watch?v=7R6Odp_PQck&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=9 Лекция Ytb</ins>]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
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Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94063&oldid=prev
Mkgoldshteyn в 15:11, 5 декабря 2025
2025-12-05T15:11:55Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:11, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l89">Строка 89:</td>
<td colspan="2" class="diff-lineno">Строка 89:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] </div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция <del style="font-weight: bold; text-decoration: none;">Ytb] [https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар </del>Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td colspan="2" class="diff-side-added"></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
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Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94062&oldid=prev
Mkgoldshteyn в 15:11, 5 декабря 2025
2025-12-05T15:11:29Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:11, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l89">Строка 89:</td>
<td colspan="2" class="diff-lineno">Строка 89:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb] [https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] </div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>[https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb] [https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94060&oldid=prev
Mkgoldshteyn в 15:11, 5 декабря 2025
2025-12-05T15:11:04Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:11, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l89">Строка 89:</td>
<td colspan="2" class="diff-lineno">Строка 89:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb][https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb] [https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар Ytb]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94059&oldid=prev
Mkgoldshteyn в 15:10, 5 декабря 2025
2025-12-05T15:10:36Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:10, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l89">Строка 89:</td>
<td colspan="2" class="diff-lineno">Строка 89:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар VK<ins style="font-weight: bold; text-decoration: none;">] [https://www.youtube.com/watch?v=OIWZnWtw_Eg&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=7 Лекция Ytb][https://www.youtube.com/watch?v=MSPbBngj8ec&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=6 Семинар Ytb</ins>]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94058&oldid=prev
Mkgoldshteyn в 15:09, 5 декабря 2025
2025-12-05T15:09:24Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:09, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l89">Строка 89:</td>
<td colspan="2" class="diff-lineno">Строка 89:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''9''' || Discrete VAE, VQ-VAE, VQ-VAE2, likelihood free-learning, GANs || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239577?linked=1 Лекция VK]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec5_vqvae_gans.pdf Лекция]||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар <ins style="font-weight: bold; text-decoration: none;">VK</ins>] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94057&oldid=prev
Mkgoldshteyn в 15:08, 5 декабря 2025
2025-12-05T15:08:11Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:08, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l81">Строка 81:</td>
<td colspan="2" class="diff-lineno">Строка 81:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''5''' || Технологии современных LLM (Rope, KV-cache), Reasoning, RAG, Open-source LLM|| [Лекция] [Семинар] || [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''5''' || Технологии современных LLM (Rope, KV-cache), Reasoning, RAG, Open-source LLM|| [Лекция] [Семинар] || [Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''6''' || Нормализующие потоки, авторегрессионные и линейные потоки, модели NICE, RealNVP и Glow|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239512?linked=1 Лекция VK] [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239513?linked=1 Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec2_flows.pdf Лекция] [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/seminars/pro/sem2_flow.ipynb Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/homeworks/pro/hw2/hw2.ipynb Glow]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''6''' || Нормализующие потоки, авторегрессионные и линейные потоки, модели NICE, RealNVP и Glow|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239512?linked=1 Лекция VK] [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239513?linked=1 Семинар <ins style="font-weight: bold; text-decoration: none;">VK</ins>] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec2_flows.pdf Лекция] [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/seminars/pro/sem2_flow.ipynb Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/homeworks/pro/hw2/hw2.ipynb Glow]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''7''' || Модели скрытых переменных, ЕМ-алгоритм, вывод вариационной нижней оценки (ELBO)|| [https://m.vkvideo.ru/video-227011779_456239540?t=21m48s Лекция]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec3_lvm.pdf Лекция VK] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''7''' || Модели скрытых переменных, ЕМ-алгоритм, вывод вариационной нижней оценки (ELBO)|| [https://m.vkvideo.ru/video-227011779_456239540?t=21m48s Лекция]|| [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec3_lvm.pdf Лекция VK] ||</div></td></tr>
<tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l91">Строка 91:</td>
<td colspan="2" class="diff-lineno">Строка 91:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''10''' || Проблемы GANs: Mode collapse, Manifold Hypotesis; Wasserstain Distance, WGAN, WGAN-GP, PG-GAN, SAGAN, StyleGAN|| [https://m.vkvideo.ru/video-227011779_456239598 Лекция VK] [https://m.vkvideo.ru/video-227011779_456239612?t=50m4s Семинар] || [https://github.com/NickKar30/GM-HSE-AI-masters-course/blob/main/lectures/pro/lec6_gans.pdf Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] || [Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK<ins style="font-weight: bold; text-decoration: none;">] [https://www.youtube.com/watch?v=O7KdDHsaY5w&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=4 Лекция Ytb</ins>]|| [Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''12''' || Прямой и обратный диффузионные процессы, диффузия как модель VAE || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239631?linked=1&t=40m38s Лекция VK] [Семинар VK] [https://www.youtube.com/watch?v=VsF0MU-6754&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=2 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''12''' || Прямой и обратный диффузионные процессы, диффузия как модель VAE || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239631?linked=1&t=40m38s Лекция VK] [Семинар VK] [https://www.youtube.com/watch?v=VsF0MU-6754&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=2 Лекция Ytb]|| [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94056&oldid=prev
Mkgoldshteyn в 15:07, 5 декабря 2025
2025-12-05T15:07:00Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:07, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l93">Строка 93:</td>
<td colspan="2" class="diff-lineno">Строка 93:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] || [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''11''' || Energy based models, динамика Ланжевена, score matching: Implicit score matching, sliced score matching, denoising score matching, Noise conditioned score network|| [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239621?linked=1&t=1h15m13s Лекция VK] || [Лекция] [Семинар] ||</div></td></tr>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''12''' || Прямой и обратный диффузионные процессы, диффузия как модель VAE || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239631?linked=1&t=40m38s Лекция VK] [Семинар] || [Лекция] [Семинар] ||</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''12''' || Прямой и обратный диффузионные процессы, диффузия как модель VAE || [https://vkvideo.ru/playlist/-227011779_46/video-227011779_456239631?linked=1&t=40m38s Лекция VK] [Семинар <ins style="font-weight: bold; text-decoration: none;">VK] [https://www.youtube.com/watch?v=VsF0MU-6754&list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9&index=2 Лекция Ytb</ins>]|| [Лекция] [Семинар] ||</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|-</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''13''' || || [Лекция] [Семинар] || [Лекция] [Семинар] ||</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| style="background:#eaecf0;" | '''13''' || || [Лекция] [Семинар] || [Лекция] [Семинар] ||</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94055&oldid=prev
Mkgoldshteyn в 15:03, 5 декабря 2025
2025-12-05T15:03:40Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:03, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l25">Строка 25:</td>
<td colspan="2" class="diff-lineno">Строка 25:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на VK: [https://vkvideo.ru/playlist/-227011779_46 VK-playlist]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на VK: [https://vkvideo.ru/playlist/-227011779_46 VK-playlist]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на YouTube: [https://www.youtube.com/playlist?list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9]</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на YouTube: [https://www.youtube.com/playlist?list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9 <ins style="font-weight: bold; text-decoration: none;">YouTube-playlist</ins>]</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на GitHub с материалами курса: [https://github.com/NickKar30/GM-HSE-AI-masters-course GitHub]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на GitHub с материалами курса: [https://github.com/NickKar30/GM-HSE-AI-masters-course GitHub]</div></td></tr>
</table>
Mkgoldshteyn
https://wiki.cs.hse.ru/index.php?title=%D0%93%D0%B5%D0%BD%D0%B5%D1%80%D0%B0%D1%82%D0%B8%D0%B2%D0%BD%D1%8B%D0%B5_%D0%BC%D0%BE%D0%B4%D0%B5%D0%BB%D0%B8_%D0%B2_%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%BD%D0%BE%D0%BC_%D0%BE%D0%B1%D1%83%D1%87%D0%B5%D0%BD%D0%B8%D0%B8_(%D0%98%D0%98_2025)&diff=94054&oldid=prev
Mkgoldshteyn в 15:03, 5 декабря 2025
2025-12-05T15:03:10Z
<p></p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<col class="diff-marker" />
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<col class="diff-marker" />
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<tr class="diff-title" lang="ru">
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Предыдущая версия</td>
<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Версия от 15:03, 5 декабря 2025</td>
</tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l24">Строка 24:</td>
<td colspan="2" class="diff-lineno">Строка 24:</td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Материалы курса ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Материалы курса ==</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на VK: [https://vkvideo.ru/playlist/-227011779_46 VK-playlist]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на плейлист курса на VK: [https://vkvideo.ru/playlist/-227011779_46 VK-playlist]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Ссылка на плейлист курса на YouTube: [https://www.youtube.com/playlist?list=PLmA-1xX7IuzC-MkRlR8XdGJQlQUKigDR9]</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на GitHub с материалами курса: [https://github.com/NickKar30/GM-HSE-AI-masters-course GitHub]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Ссылка на GitHub с материалами курса: [https://github.com/NickKar30/GM-HSE-AI-masters-course GitHub]</div></td></tr>
</table>
Mkgoldshteyn