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2025

[CS236] 9. GANs - 1 08-27
[CS236] 8. Normalizing Flows - 2 08-10
[CS236] 7. Normalizing Flows - 1 08-07
[CS236] 6. Latent Variable Models-2 07-26
[CS236] 5. Latent Variable Models-1 07-14
[CS236] 4. Maximum Likelihood Learning 06-30
[CS236] 3. Autoregressive Models 05-07
[CS236] 2. Background 04-20
[Paper Review]Diffusion Models Beat GANs on Image Synthesis(ADM-G) 02-28
[Paper Review]High-Resolution Image Synthesis with Latent Diffusion Models(LDM) 02-17
[Paper Review]Denoising Diffusion Implicit Models(DDIM) 02-13
[Paper Review]Denoising Diffusion Probabilistic Models(DDPM) 01-15

2024

[Paper Review]Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks(DCGAN) 09-13
[Paper Review]Generative Adversarial Nets(GAN) 09-02
[Paper Review]Multimodal Machine Learning: A Survey and Taxonomy 08-29
[Paper Review]Auto-Encoding Variational Bayes(VAE) 08-26
[CS231n] 10. Recurrent Neural Networks 08-21
[Paper Review]Training data-efficient image transformers & distillation through attention(DeiT) 08-18
[CS231n] 09.CNN Architectures 08-11
[Paper Review]AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE(ViT) 07-31
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