GANs
- What is the difference between generative model and discriminative models
- KL Divergence - Kullback-Leibler Divergence
- F-Divergence
- Convex conjugate (also known as the Fenchel conjugate or the Legendre transform)
- GANs
- Naive GANs
- Wasserstein metric
- Wasserstein GANs
- Frechet Inception Distance (FID)
- Conditional GANs(cGANs)
- Domain adversarial networks
VAEs
- Variational encoding(VAEs)
- Two types of neural networks
- Aggregated posterior mismatch
- VAE as regularized autoencoder and Beta VAEs
- Info VAEs
- Vector Quantized VAEs (VQ-VAEs)
DDPM
- Denoising Diffusion Probabilistic Models (DDPM) - part 1
- Denoising Diffusion Probabilistic Models (DDPM) - part 2
- Denoising Diffusion Probabilistic Models (DDPM) - part 3
- Summarizing DDPM
Score matching
- Score matching part 1
- Score matching part 2
- Score matching part 3
- Difference between SMLD and DDPM
- Conditional score matching
SDEs
- Precursor to Stochastic Differential Equations (SDEs)
- Stochastic Differential Equations (SDEs)
- Some example problems
- Anderson’s result
- DDPMs as SDE
- SMLD as SDE
- Main takeaway
- DDIM
- DDIM inversion
Sequence2sequence models
Self supervised learning
- Noise contrastive estimation
- Info-NCE
- Masked reconstruction
- JEPA - Joint Embedding Prediction and Autoencoding