Generative Deep Learning, 2nd Edition

Index

Symbols

• 1-Lipschitz continuous function, The Lipschitz Constraint

A

• accuracy, determining, The Discriminator, ChatGPT, Large Language Models, Generative AI Ethics and Challenges
• action, in reinforcement learning, Reinforcement Learning
• activation functions, Layers
• active inference, Final Thoughts
• Adam (Adaptive Moment Estimation) optimizer, Optimizers
• adaptive instance normalization (AdaIN), Adaptive instance normalization, Weight Modulation and Demodulation
• agent, in reinforcement learning, Reinforcement Learning
• AI (artificial intelligence), Generative Modeling and AI, Final Thoughts
• AI ethics, Generative AI Ethics and Challenges-Generative AI Ethics and Challenges
• approximate density models, Generative Model Taxonomy
• artifacts, The Generator, StyleGAN2
• artificial intelligence (AI), Generative Modeling and AI, Final Thoughts
• artificial neural networks (ANNs), Deep Neural Networks
• arXiv, Other Resources
• “Attention Is All You Need” (Vaswani), Introduction, 2014–2017: The VAE and GAN Era
• attention mechanisms
  • attention equation, Queries, Keys, and Values
  • attention head, Attention
  • attention scores, Viewing the attention scores
  • attention weights, Queries, Keys, and Values
  • generating polyphonic music, Tokenization of Polyphonic Music
  • paper popularizing, Introduction
  • self- versus cross-referential, T5
  • understanding, Attention
• attribute binding, Limitations
• attributes, entangled, StyleGAN
• AudioLM, Other Applications
• “Auto-Encoding Variational Bayes” (Kingma and Welling), Variational Autoencoders
• autoencoders