Generative Model-Course Introduction
Introduction
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Course Support
Generative Model-Probability for Generative Models
Generative Space
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Joint Probability for Generative Models
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Sampling from a Joint Probability Distribution
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Conditional Probability for Generative Models
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The Chain Rule of Probabilities
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Generative Model-Generative vs. Discriminative Models
1D Example: Generative vs. Discriminative Models
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1D Example: Sampling
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2D Example: Generative vs. Discriminative Models
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Generative Adversarial Network (GAN)-Overview
Generative Adversarial Networks (Abstract)
Motivation of Studying GAN
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Generative Adversarial Network (GAN)-Generator and Discriminator
Distributions
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Drawing Pins
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GAN Architecture
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Generative Adversarial Network (GAN)-Training GANs
Autoencoder
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Generative "Comparative" Network
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Generative "Adversarial" Network
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Visualizing GAN Loss
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Calculating GAN Loss
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Language Model-Language Model Foundation
Language Model
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Auto-Regressive Model
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Language Model-Transformer's Attention Mechanism
Attention Is All You Need (Abstract)
Encoder-Decoder RNN
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Attention
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Cross-Attention
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Self-Attention
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Language Model-Transformer's Architecture
Embeddings
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Positional Encoding
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Output Probabilities
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Encoder
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Decoder
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Language Model-ChatGPT
GPT-4 Technical Report (Abstract)
Training Language Models to Follow Instructions with Human Feedback (Abstract)
Pre-training vs. Supervised Fine-Tuning
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Reinforcement Learning with Human Feedback
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Image Model-Probabilistic Image Models
Smurfs
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Pixel-based Image Model
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Autoregressive Image Model
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Training an Autoregressive Image Model
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Image Model-Diffusion Model
Denoising Diffusion Probabilistic Models (Abstract)
Impact
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