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A (long) introduction to neural nets, and popular options of CNNs, RNNs, Transformers, and other modern machine learning models, including generative models (generative adversarial networks, variational autoencoders, and diffusion models), state space models, graph neural networks, deep reinforcement learning, and ethical and societal implications

A brief review of my predoc applications during AY 2024–2025

Times New Roman, Palatino, Garamond, Erewhon, Georgia

Using pairwise comparison data to assess abilities

A quick guide to LaTeX