Difference between revisions of "Course syllabus: Generative deep learning"
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| − | ===Classes== | + | {{#seo: |
| + | |title=Generative Deep Learning - course syllabus | ||
| + | |titlemode=replace | ||
| + | |keywords=Generative Deep Learning | ||
| + | |description=The course Generative Deep Learning is devoted to Autoregressive models, the Bayesian framework, latent variable models, and the EM algorithm. | ||
| + | }} | ||
| + | ==Classes== | ||
# 02.09 Autoregressive models (MADE, WaveNet, PicelCNN) | # 02.09 Autoregressive models (MADE, WaveNet, PicelCNN) | ||
# 09.09 Bayesian framework. Latent variable models, EM-algorithm | # 09.09 Bayesian framework. Latent variable models, EM-algorithm | ||
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# 09.12 Continious-in-time models (NeuralODE, FFjord), Quantized latent models (VQ-VAE, VQ-VAE-2, FQ-GAN). | # 09.12 Continious-in-time models (NeuralODE, FFjord), Quantized latent models (VQ-VAE, VQ-VAE-2, FQ-GAN). | ||
| − | + | ==Homeworks== | |
# Autoregressive models 28.09 | # Autoregressive models 28.09 | ||
# Latent variable models, Flows 12.10 | # Latent variable models, Flows 12.10 | ||
# Autoregressive flows, Flows in VAE 26.10 | # Autoregressive flows, Flows in VAE 26.10 | ||
# GAN, WGAN09 11 | # GAN, WGAN09 11 | ||
Latest revision as of 23:50, 13 February 2024
Classes
- 02.09 Autoregressive models (MADE, WaveNet, PicelCNN)
- 09.09 Bayesian framework. Latent variable models, EM-algorithm
- 16.09 EM-algorithm, VAE, Mean field approximation
- 23.09 Flow models (NICE, RealNVP, RevNet, i-RevNet)
- 30.09 Flow models (Glow, Flow++), Flows in VAE, Autoregressive flows (IAF)
- 07.10 Autoregressive flows (IAF, MAF, Parallel WaveNet), ELBO surgery,
- 14.10 VampPrior, Posterior collapse (PixelVAE, VLAE), Decoder weakening, IWAE
- 21.10 Vanila GAN, Vanishing gradients, mode collapse, KL vs JSD, DCGAN, Wasserstein distance
- 28.10 Wasserstein GAN, Spectral Normalization GAN, f-divergence#10 11.11 GAN evaluation, Advanced GANs (SAGAN, BigGAN, ProGAN, StyleGAN)
- 25.11 Disentanglement (InfoGAN, beta-VAE, DIP-VAE, FactorVAE)
- 09.12 Continious-in-time models (NeuralODE, FFjord), Quantized latent models (VQ-VAE, VQ-VAE-2, FQ-GAN).
Homeworks
- Autoregressive models 28.09
- Latent variable models, Flows 12.10
- Autoregressive flows, Flows in VAE 26.10
- GAN, WGAN09 11