├── 0 - Index.md ├── 1- What is the difference between generative model and discriminative model.md ├── 10 - Conditional GANs.md ├── 11 - Domain adversarial networks.md ├── 11.JPG ├── 12 - Variational encoding.md ├── 12.1 - Two types of NNs.md ├── 12.JPG ├── 13 - Aggregated posterior mismatch .md ├── 13.JPG ├── 14 - VAE as regularized autoencoder.md ├── 14.1 Info VAE.md ├── 15 - VQVAE.md ├── 16 - Denoising Diffusion Probabilistic Models (DDPM) - part 1.md ├── 16.JPG ├── 17 - Denoising Diffusion Probabilistic Models (DDPM) - part 2.md ├── 18 - Denoising Diffusion Probabilistic Models(DDPM) - part 3.md ├── 18.JPG ├── 19 - Summarizing DDPM.md ├── 19.JPG ├── 2 - KL Divergence - Kullback-Leibler Divergence.md ├── 20 - Score matching part 1.md ├── 20.JPG ├── 21 - Score matching part 2.md ├── 21.JPG ├── 22 - Score matching part 3.md ├── 22.JPG ├── 23 - Difference between SMLD and DDPM.md ├── 24 - Conditional score matching.md ├── 24.JPG ├── 25- Precursor to Stochastic Differential Equations (SDEs).md ├── 25.JPG ├── 26 - Stochastic Differential Equations (SDEs).md ├── 26.1 - Some example problems.md ├── 26.2 Anderson's result.md ├── 26.JPG ├── 27 DDPM as SDEs.md ├── 27.JPG ├── 28 - SMLD as SDE.md ├── 28.JPG ├── 29 - Main takeaway.md ├── 3 - F Divergence.md ├── 3.PNG ├── 30 - DDIM.md ├── 30.JPG ├── 31 - DDIM inversion.md ├── 32 State space models.md ├── 32.JPG ├── 33 - Noise contrastive estimation.md ├── 33.JPG ├── 34 - Info-NCE.md ├── 34.JPG ├── 35 - Masked reconstruction.md ├── 36 - JEPA.md ├── 36.JPG ├── 37 - Distillation.md ├── 37.JPG ├── 38.JPG ├── 39.JPG ├── 4 - Convex conjugate.md ├── 4.JPG ├── 4.PNG ├── 40.JPG ├── 41.JPG ├── 42.PNG ├── 5 - GANs.md ├── 5.JPG ├── 5.PNG ├── 6 - Naive GANs.md ├── 6.PNG ├── 7 -Wasserstein metric.md ├── 8 - Wasserstein GANs .md ├── 9 -Frechet inception distance.md ├── 9.JPG ├── Deep Learning book.pdf ├── README.md └── Transformers ├── 1.JPG ├── 1.pdf ├── 31.5.md ├── 4.JPG ├── 5.JPG ├── 6.JPG └── 7.JPG /0 - Index.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/victor-explore/Deep-Learning-Lecture-Notes-IISC-Banglore/HEAD/0 - 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Domain adversarial networks.md -------------------------------------------------------------------------------- /11.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/victor-explore/Deep-Learning-Lecture-Notes-IISC-Banglore/HEAD/11.JPG -------------------------------------------------------------------------------- /12 - Variational encoding.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/victor-explore/Deep-Learning-Lecture-Notes-IISC-Banglore/HEAD/12 - Variational encoding.md -------------------------------------------------------------------------------- /12.1 - Two types of NNs.md: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/victor-explore/Deep-Learning-Lecture-Notes-IISC-Banglore/HEAD/12.1 - Two types of NNs.md -------------------------------------------------------------------------------- /12.JPG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/victor-explore/Deep-Learning-Lecture-Notes-IISC-Banglore/HEAD/12.JPG -------------------------------------------------------------------------------- /13 - 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