Time- and space-continuous neural PDE forecaster based on INRs and ODEs

Taylor-mode automatic differentiation for higher-order derivatives

The link to the website https://phogroup.github.io/

Control barrier functions (CBFs) and control Lyapunov functions (CLFs) written in Julia.

Kolmogorov Arnold Networks

Python Version of F-16 Maneuver Verification Benchmark

A python library for generating PDF XDSM diagrams.

Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks

Julia Implementation of the nonintrusive model reduction approaches: Operator Inference (OpInf) and Lift & Learn (LnL)

Medium fidelity aircraft-propulsion system design and optimization.

Hamilton-Jacobi reachability analysis in JAX.

Julia package for computing Hamilton-Jacobi Reachability of optimal 2-player (control/disturbance) differential games via Hopf optimization

Playing Pokemon Red with Reinforcement Learning

Introduction to machine learning course Dr. Tan Bui (reference: Teaching materials for the applied machine learning course at Cornell Tech)

Structure Preserving Machine Learning Models in Julia

Computational Fluid Dynamics in JAX

An inverse game solver for inferring objectives from noise-corrupted partial state observations of non-cooperative multi-agent interactions.

A low latency guitar effects processor suitable for running on a raspberry pi

Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains

OpenConcept: A toolkit for conceptual MDAO of aircraft with unconventional propulsion architectures