code

I’m a big believer in reproducible science and open-source software. In line with this, below are some pieces of code that I’ve written, listed in reverse-chronological order.

The latest code is mostly based on neural network libraries in Python such as jax and PyTorch, with applications in high-dimensional scientific computing and generative modeling.

The earlier code is written in C++ (or even FORTRAN) and is parallelized with openmp or MPI, with applications in large-scale modeling and simulation of disordered systems from statistical physics and continuum mechanics.

1. model-free probability flows (with Eric Vanden Eijnden)
2. structured diffusion (with Arthur Jacot and Stephen Tu)
3. flow map matching (with Michael Albergo and Eric Vanden Eijnden)
4. forecasting with interpolants (with Mengjian Hua, Yifan Chen, Mark Goldstein, Eric Vanden Eijnden, and Michael Albergo – mostly written by the first three authors!)
5. active probability flows (with Eric Vanden Eijnden)
6. stochastic interpolants (with Michael Albergo and Eric Vanden Eijnden)
7. score-based transport modeling (with Eric Vanden Eijnden)
8. spin glass evolutionary dynamics (with Yipei Guo, Chris Rycroft, and Ariel Amir)
9. shear transformation zone++ (with Chris Rycroft)
10. real-space Hartree-Fock (with Amir Natan, note: only the Hartree-Fock implementation)