IvanYashchuk / jax-firedrake
Differentiable interface to Firedrake for JAX
☆14Updated 4 years ago
Alternatives and similar repositories for jax-firedrake:
Users that are interested in jax-firedrake are comparing it to the libraries listed below
- Differentiable interface to FEniCS for JAX☆53Updated 3 years ago
- Code for the paper "Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks" (https://arxiv.org/abs/2206.…☆10Updated 2 years ago
- Easy interoperability with Automatic Differentiation libraries through NumPy interface to Firedrake and FEniCS☆15Updated last year
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆94Updated last year
- Efficient forward- and reverse-mode sparse Jacobians using Jax☆55Updated 5 months ago
- Rescure useful code in TensorNetwork by google for further personal usage.☆11Updated 5 months ago
- An example showing how to use jax to train resnet50 on multi-node multi-GPU☆20Updated 2 years ago
- Reverse-mode AD of dominant sparse eigensolver using Pytorch.☆39Updated 4 years ago
- Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"☆14Updated 2 years ago
- Turning SymPy expressions into JAX functions☆45Updated 4 years ago
- Forward mode laplacian implemented in JAX tracer☆29Updated 2 months ago
- Code to estimate Renormalized Mutual Information in simple settings☆13Updated 4 years ago
- ☆31Updated 4 years ago
- Orthogonal polynomials with JAX☆22Updated this week
- No need to train, he's a smooth operator☆44Updated 5 months ago
- Efficient Differentiable n-d PDE solvers in JAX.☆28Updated 6 months ago
- Ab-initio simulation of interacting fermions with equivariant normalizing flow.☆34Updated 2 years ago
- Website for the book "The Elements of Differentiable Programming".☆13Updated 8 months ago
- Code for paper https://arxiv.org/abs/2306.07961☆53Updated 10 months ago
- ☆19Updated last year
- ☆28Updated 3 years ago
- generative neural network trained with physics knowledge☆14Updated 4 years ago
- Fast extremal eigensolvers for PyTorch.☆17Updated 3 years ago
- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.☆55Updated last month
- Hierarchical variational models for physics.☆17Updated 4 years ago
- A software package for flexible HPC GPs☆16Updated last week
- Use numba-compiled kernels from within Jax☆27Updated last week
- Automatic Differentiation for Solid Mechanics☆55Updated 5 months ago
- ☆10Updated 4 years ago
- Checkpointing for Automatic Differentiation☆53Updated this week