notes
Technical
Math
Numerical Methods for SDEs
I am in the process of writing a mathematically rigorous introduction to numerical SDEs (TODO):
- Numerical SDEs 1: Finite Difference Methods for ODEs and PDEs
- Numerical SDEs 2: Intro to Strong Approximations for SDEs
- Numerical SDEs 3: Advanced Strong Approximations for SDEs and Stochastic Filtering
- Numerical SDEs 4: Intro to Weak Approximations for SDEs
- Numerical SDEs 5: Advanced Weak Approximations for SDEs and Monte Carlo Estimation
Physics
- Everaise: Physics: Most of my notes for (competition) physics can be found here.
- An Introduction to Diffusion Monte Carlo: TODO
Course Notes
During my time at MIT, I maintained a list of both notes and "cheatsheets" for technical classes I took as a way of summarizing my understanding. Typically, I edit my notes post-hoc so they are a bit more in-depth than the course content (and cover broader things than just the course content) while my cheatsheets simply give a broad overview of the course content. Most of the notes are still a work in progress.
A full list of coursework can be found here.
Notes
- 6.867: Machine Learning
- 18.675: Theory of Probability (Incomplete)
- 18.676: Stochastic Calculus (Incomplete)