Approximation Theory of Neural Networks
Integral test for the series - Technique used in this paper
Approximation theory (Theorem 5) in Schmidt-Hieber, 2020
A nice introductory note for analytic function
Neural Net is a Universal Function Approximator, YouTube Video
Learning Theory / Empirical Process Theory
Bounds on Symmetrization and De-symmetrization
Vershynin's Lecture on High-dimensional probability
Stanford CS229M
Martingales
Neural Network / Diffusion model
Derivation of DDPM (Lil's blog)
Useful Tutorial Video in Korean , Yang Song's Talk
Introduction on Continuous Time Markov Chain - Discrete Denoising Model .
Reverse SDE proof by Fokker-Planck Eqn.
Intuition on U-net in DDPM
U-net for image segmentation
Score Matching Diffusion Model
Stanley Chan's Note for diffusion model
Nice intuition on the classifier-guidance technique from Sander Dieleman
Diffusion Model & Flow Matching
Large Language Models
Karpathy's lecture: Busy person's intro to LLM
Tutorial on Transformer, Video on Transformer
My Implementation of Transformer
Auxiliary
Andrew Ng's secret to mastering ML
Diffusion Model for time series data
Elon Musk's vision in 2007
Stephen Curry's France Olympic Final Highlight