Alternatives and similar repositories for jax-firedrake:

Users that are interested in jax-firedrake are comparing it to the libraries listed below

• IvanYashchuk / fecr
  Easy interoperability with Automatic Differentiation libraries through NumPy interface to Firedrake and FEniCS
  ☆15Updated last year
• IvanYashchuk / jax-fenics
  Differentiable interface to FEniCS for JAX
  ☆53Updated 3 years ago
• eepperly / XTrace
  Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"
  ☆13Updated last year
• IvanYashchuk / jax-fenics-adjoint
  Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint
  ☆93Updated last year
• RehMoritz / vmc_pde
  Code for the paper "Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks" (https://arxiv.org/abs/2206.…
  ☆10Updated 2 years ago
• buwantaiji / DominantSparseEigenAD
  Reverse-mode AD of dominant sparse eigensolver using Pytorch.
  ☆39Updated 4 years ago
• y1xiaoc / fwdlap
  Forward mode laplacian implemented in JAX tracer
  ☆29Updated last month
• SciML / OperatorLearning.jl
  No need to train, he's a smooth operator
  ☆44Updated 5 months ago
• lukasheinrich / pyhep2020-autodiff-tutorial
  ☆31Updated 4 years ago
• YichengDWu / Sophon.jl
  Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks
  ☆55Updated 3 weeks ago
• mfschubert / sparsejac
  Efficient forward- and reverse-mode sparse Jacobians using Jax
  ☆55Updated 4 months ago
• avigliotti / AD4SM.jl
  Automatic Differentiation for Solid Mechanics
  ☆55Updated 4 months ago
• diffprog / diffprog.github.io
  Website for the book "The Elements of Differentiable Programming".
  ☆13Updated 7 months ago
• Ceyron / exponax
  Efficient Differentiable n-d PDE solvers in JAX.
  ☆28Updated 5 months ago
• qiyang-ustc / jaxeigs
  Rescure useful code in TensorNetwork by google for further personal usage.
  ☆11Updated 4 months ago
• lsarra / rmi
  Code to estimate Renormalized Mutual Information in simple settings
  ☆13Updated 4 years ago
• rfeinman / Torch-ARPACK
  Fast extremal eigensolvers for PyTorch.
  ☆17Updated 3 years ago
• aced-differentiate / EquivariantOperators.jl
  ☆19Updated last year
• kailaix / PhysGNN
  generative neural network trained with physics knowledge
  ☆14Updated 4 years ago
• refraction-ray / admc
  Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution
  ☆23Updated 2 years ago
• SciML / DeepEquilibriumNetworks.jl
  Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
  ☆54Updated 3 weeks ago
• gaurav-arya / differentiable_mh
  Code for paper https://arxiv.org/abs/2306.07961
  ☆53Updated 9 months ago
• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆21Updated 8 months ago
• Argonne-National-Laboratory / Checkpointing.jl
  Checkpointing for Automatic Differentiation
  ☆53Updated this week
• DENG-MIT / StiffNeuralODE
  Stiff Neural Ordinary Differential Equations
  ☆32Updated last year
• MilesCranmer / sympy2jax
  Turning SymPy expressions into JAX functions
  ☆44Updated 4 years ago
• kailaix / AdFem.jl
  Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling
  ☆83Updated 3 years ago
• PhilipVinc / Jax.jl
  ☆28Updated 3 years ago
• JuliaApproximation / ApproxFunExamples
  Examples for using ApproFun.jl
  ☆25Updated 3 months ago
• KindXiaoming / NNPhD-github
  Code for "Machine-Learning Non-Conservative Dynamics for New-Physics Detection" (arXiv: 2106.00026)
  ☆15Updated 3 years ago