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
Tutorial on Transformer, Video on Transformer
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
Auxiliary
Andrew Ng's secret to mastering ML
Diffusion Model for time series data
Elon Musk's vision in 2007