Fast and Easy Infinite Neural Networks in Python

[ICML2022] Variational Wasserstein gradient flow

Pytorch implementation of DGflow (ICLR 2021).

Numeric simulation of a 2D Bose Einstein condensate

[NeurIPS 2022] Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again by Ajay Jaiswal*, Peihao Wang*, Tianlong Chen, Justin F Rousseau, Ying Ding, Zhangyang Wang

Solver for differential algebraic equations

Variational Filtering via Wasserstein Gradient Flow

[NeurIPS'25] Sequence Modeling with Spectral Mean Flows, in PyTorch

Senior Project for Statistics & Data Science at Yale University

Accelerated Stein Variational Gradient Descent for sampling for densities

Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.

MILC collaboration's fork of the Quantum EXpressions lattice field theory framework

Yale S&DS 432 final project studying lazy training dynamics for differentiable optimization problems

Code for paper: "Improved Residual Network Based on Norm-Preservation for Visual Recognition" https://doi.org/10.1016/j.neunet.2022.10.023

Cobebase for my paper "Convergence of Shallow ReLU Networks on Weakly Interacting Data", accepted at NeurIPS 2025

A continuous-time geometric formulation of sorting as gradient flow on the permutohedron

Discrete approximation to 3D winding number mapping T^3->U(N)

Analysis of the anisotropic Gradient Flow output of 1203.4469 for anisotropic lattice QCD gauge anisotropy determination and scale setting

Utilities of quantum theory of (higher-form) general gauge fields