Data-driven reduced order modeling for nonlinear dynamical systems

Minimal and Clean Reinforcement Learning Examples

Accelerated Differentiable Optimization with MadNLP

Elegant and Performant Deep Learning

Modular simulation library for AI datacenter-grid interaction

Small Foundation Models for the Power Grid

Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules

Training non-differentiable networks via optimal transport.

Electrical power system simulation tool primarily for utility power distribution systems

OpenDSSDirect.py: a cross-platform Python package that implements a native/direct library interface to the alternative OpenDSS engine from DSS-Extensions.org

A time & energy benchmark suite for generative AI

The Prodigy optimizer and its variants for training neural networks.

D-Adaptation for SGD, Adam and AdaGrad

Building Optimization Performance Tests

Code supplement to "Integrated Investment and Policy Planning for Power Systems via Differentiable Scenario Generation"

Data-Driven Distributionally Robust AC Optimal Power Flow for Radial Distribution Systems : Code Supplement

Differentiable network optimization

Optimal Control and Learning Course

Sampling Decisions

This is the implementation of the paper DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty

RTE provides here an access to the structural French grid data with detailed topology time series, updated at 5-minute intervals. However, sensitive information such as specific injections and powe…

Access data from RTE API

Official implementation of Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization (ICLR 2026).

Convert CVXPY expressions to PyTorch expressions

Fully First-Order Differentiable Optimization

PyTorch implementation of machine unlearning [torchunlearn] @ NeurIPS 2025 "Unlearning-Aware Minimization"