| Nov 2023 | Machine Learning literature🧮 math |
| Aug 2023 | Topics in Bayesian Machine Learning🧮 math |
| Aug 2023 | The Gaussian Cheatsheet🧮 math |
| Aug 2023 | Diffusion Models🧮 math |
| Jul 2023 | Hypothesis Testing🧮 math |
| Jun 2023 | Cross-Entropy, Label Smoothing, and Focal Loss🧮 math |
| Jun 2023 | Differential Entropy🧮 math |
| May 2023 | Higher-order gradients in PyTorch, Parallelized🧮 math |
| May 2023 | Notes on OOD Generalization🧮 math |
| May 2023 | Raw notes on Interpretable Machine Learning🧮 math |
| May 2023 | Gradient Boosted Decision Trees: A Recap🧮 math |
| May 2023 | Decision Theory🧮 math |
| May 2023 | Beyond Bayes🧮 math |
| May 2023 | Mathematics Overview🧮 math |
| Dec 2022 | Topics in Numerical Analysis🧮 math |
| Apr 2022 | Machine Learning courses🧮 math |
| Dec 2020 | The Gibbs distribution and general Bayes🧮 math |
| Nov 2020 | Why is Bayesian inference hard?🧮 math |
| Sep 2020 | Orthogonal projectors and linear regression🧮 math |
| Aug 2020 | Discovering Taylor series the hard way🧮 math |
| Aug 2020 | Linear Algebra Done Right🧮 math |
| Aug 2020 | ML Fragments🧮 math |
| Jul 2020 | An Introduction to Epipolar Geometry🧮 math |
| Jul 2020 | RL: Tricks of the Trade🧮 math |
| Feb 2020 | Deriving the Cross Entropy Method🧮 math |
| Mar 2019 | The Stein Gradient🧮 math |
| May 2018 | Policy Gradients in a Nutshell🧮 math |
| Feb 2018 | When does SGD work well?🧮 math |
| Dec 2017 | The beauty of Bayesian Learning🧮 math |
| Oct 2017 | Visualizing the Confusion Matrix🧮 math |
| Oct 2017 | The magic of Automatic Differentiation🧮 math |
| Jul 2017 | A Primer on Projective Geometry🧮 math |
| Jun 2017 | Introduction to RANSAC🧮 math |
