differentiable-physics

AeroJAX: A differentiable, structure-preserving framework for real-time flow simulation, control, and inverse design. Architected for neural operator integration and latent-space acceleration. Built with JAX.

Efficient Differentiable n-d PDE Solvers in JAX.

Universal components for differentiable scientific computing. 📦

Incompressible Navier-Stokes solver

[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)

A library for soft differentiable relaxations of common JAX functions.

[IROS 2024] [ICML 2024 Workshop Differentiable Almost Everything] MonoForce: Learnable Image-conditioned Physics Engine

Electromagnetics simulation library for moving point charges built on JAX

A library for soft differentiable relaxations of common PyTorch functions.

Verifier-first transfer-matrix workbench for multilayer optics and differentiable inverse design

[NeurIPS 2024] NeuMA: Neural Material Adaptor for Visual Grounding of Intrinsic Dynamics

A simple JAX-powered simulation library for numerical experiments of fuzzy dark matter, stars, gas + more!

Differentiable Flexible Mechanical Metamaterials

This repo contains the differentiable physics simulation module in "PPR: Physically Plausible Reconstruction from Monocular Videos". ICCV 23.

Universal Partial Differential Equations Simulator

Repository for MHPI differentiable hydrological models.

Generic framework for building differentiable models.

A benchmark suite and re-usable collection of differentiable physics solvers.

Simple differentiable approximate ocean models built with JAX.

Training methodologies for autoregressive neural operators/emulators in JAX.