tumaer / jax-sphLinks
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework
☆75Updated 8 months ago
Alternatives and similar repositories for jax-sph
Users that are interested in jax-sph are comparing it to the libraries listed below
Sorting:
- LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite☆65Updated 8 months ago
- JAX-DIPS is a differentiable interfacial PDE solver.☆46Updated last year
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆81Updated 3 months ago
- Code repository for "Learned Turbulence Modelling with Differentiable Fluid Solvers"☆39Updated 2 years ago
- [ICLR 2024] Neural Spectral Methods: Self-supervised learning in the spectral domain.☆46Updated last year
- Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers☆163Updated 2 years ago
- ☆37Updated 3 weeks ago
- PyTorch-FEniCS interface☆102Updated 4 years ago
- Differentiable interface to FEniCS for JAX☆58Updated 4 years ago
- Neural SPH☆35Updated last year
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Spectral Neural Operator☆78Updated last year
- Pseudospectral Kolmogorov Flow Solver☆40Updated last year
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆101Updated last year
- ☆16Updated 2 years ago
- Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics (NeurIPS '22)☆57Updated last year
- Efficient Differentiable n-d PDE solvers in JAX.☆47Updated 10 months ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆54Updated last year
- TorchFSM: Fourier Spectral Method with PyTorch☆48Updated last week
- A library for dimensionality reduction on spatial-temporal PDE☆67Updated last year
- XLB: Accelerated Lattice Boltzmann (XLB) for Physics-based ML☆392Updated last month
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆30Updated 11 months ago
- A differentiable finite element analysis solver for structural optimization based on JAX☆32Updated 2 months ago
- ☆17Updated 8 months ago
- ☆25Updated 2 years ago
- Example problems in Physics informed neural network in JAX☆81Updated 2 years ago
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆92Updated this week
- ☆27Updated last year
- Neural Emulator Architectures in JAX.☆19Updated 10 months ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆16Updated last year