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.

[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

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

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

Universal Partial Differential Equations Simulator

Generic framework for building differentiable models.

Repository for MHPI differentiable hydrological models.

Simple differentiable approximate ocean models built with JAX.

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

Training methodologies for autoregressive neural operators/emulators in JAX.