This is the overview page for area Mathematics.
Mathematics is the language of nature. Or at least the best thing that humans have at disposal to understand nature. This is a collection of posts around computer science, machine learning, reinforcement learning and other research-y topics I am involved in.
Why is Bayesian inference hard? ML & Stats in math
Machine Learning literature ML & Stats in math
Topics in Bayesian Machine Learning ML & Stats in math
Integraphs Uncategorized in math
Topics in Numerical Linear Algebra Linear Algebra in math
Orthogonal projectors and linear regression Linear Algebra in math
Discovering Taylor series the hard way Linear Algebra in math
Machine Learning courses ML & Stats in math
Machine Learning Talks & Workshops ML & Stats in math
Linear Algebra Done Right Linear Algebra in math
ML Fragments Research in math
Introducing VAR-GPs ML & Stats in math
On model interpretability and explainability Research in math
An Introduction to Epipolar Geometry Computer vision in math
RL: Tricks of the Trade Research in math
Research Workshops Research in math
The Gibbs distribution and general Bayes ML & Stats in math
The Gaussian Cheatsheet ML & Stats in math
Deriving the Cross Entropy Method Reinforcement learning in math
The Stein Gradient ML & Stats in math
Policy Gradients in a Nutshell Reinforcement learning in math
When Does Stochastic Gradient Algorithm Work Well? ML & Stats in math
The beauty of Bayesian Learning ML & Stats in math
Visualizing the Confusion Matrix ML & Stats in math
The magic of Automatic Differentiation ML & Stats in math
A Primer on Projective Geometry Computer vision in math
Introduction to RANSAC Computer vision in math
Choosing the right keys Computer science in math