This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.

Python: using OpenStudio Bindings, EnergyPlus API, and matplotlib

A differentiable PDE solving framework for machine learning

The Simulations of Navier-Stokes Equation in 2D and 3D.

My attempt at fluid simulation with the Navier Stokes equations

(EvoApps2022) "Towards a Principled Learning Rate Adaptation for Natural Evolution Strategies"

PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.

Learning in infinite dimension with neural operators.

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

How to train a neural ODE for time series/weather forecasting

浙江大学电气工程学院（自动化）课程指南

Code for our paper Demand Response Model Identification and Behavior Forecast with OptNet: a Gradient-based Approach.

Awesome machine learning for combinatorial optimization papers.

Source code for the dissertation: "Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces"

Songfang's personal webpage

Scalable Multi-Agent RL Training School for Autonomous Driving

Download an entire website from the Wayback Machine.

A command-line utility and Scrapy middleware for scraping time series data from Archive.org's Wayback Machine.