IvanYashchuk / jax-firedrake

Related projects ⓘ

Alternatives and complementary repositories for jax-firedrake

• IvanYashchuk / fecr
  Easy interoperability with Automatic Differentiation libraries through NumPy interface to Firedrake and FEniCS
  ☆14Updated 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.…
  ☆9Updated 2 years ago
• IvanYashchuk / jax-fenics
  Differentiable interface to FEniCS for JAX
  ☆50Updated 3 years ago
• f0uriest / orthax
  Orthogonal polynomials with JAX
  ☆10Updated 3 weeks ago
• IvanYashchuk / jax-fenics-adjoint
  Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint
  ☆91Updated last year
• gaurav-arya / differentiable_mh
  Code for paper https://arxiv.org/abs/2306.07961
  ☆52Updated 5 months ago
• eepperly / XTrace
  Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"
  ☆12Updated last year
• mfschubert / sparsejac
  Efficient forward- and reverse-mode sparse Jacobians using Jax
  ☆49Updated 9 months ago
• DENG-MIT / StiffNeuralODE
  Stiff Neural Ordinary Differential Equations
  ☆30Updated last year
• 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…
  ☆20Updated 4 months ago
• y1xiaoc / fwdlap
  Forward mode laplacian implemented in JAX tracer
  ☆29Updated 3 weeks ago
• PhilipVinc / Jax.jl
  ☆29Updated 2 years ago
• SciML / OperatorLearning.jl
  No need to train, he's a smooth operator
  ☆43Updated last week
• buwantaiji / DominantSparseEigenAD
  Reverse-mode AD of dominant sparse eigensolver using Pytorch.
  ☆38Updated 4 years ago
• GiggleLiu / WuLiXueBao
  WuLiXueBao magazine article - automatic differentiation.
  ☆15Updated 2 years ago
• YichengDWu / Sophon.jl
  Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks
  ☆55Updated 2 weeks ago
• nathanaelbosch / Fenrir.jl
  Physics-Enhanced Regression for Initial Value Problems
  ☆19Updated 9 months ago
• rfeinman / Torch-ARPACK
  Fast extremal eigensolvers for PyTorch.
  ☆17Updated 3 years ago
• refraction-ray / admc
  Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution
  ☆22Updated last year
• avigliotti / AD4SM.jl
  Automatic Differentiation for Solid Mechanics
  ☆54Updated 4 months ago
• diffprog / diffprog.github.io
  Website for the book "The Elements of Differentiable Programming".
  ☆13Updated 2 months ago
• MilesCranmer / sympy2jax
  Turning SymPy expressions into JAX functions
  ☆42Updated 3 years ago
• kailaix / PhysGNN
  generative neural network trained with physics knowledge
  ☆14Updated 3 years ago
• lukasheinrich / pyhep2020-autodiff-tutorial
  ☆31Updated 4 years ago
• pevnak / Unitary.jl
  A differentiable parametrization of a group of unitary matrices.
  ☆14Updated 3 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• buwantaiji / FermiFlow
  Ab-initio simulation of interacting fermions with equivariant normalizing flow.
  ☆31Updated 2 years ago
• SciML / DeepEquilibriumNetworks.jl
  Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
  ☆50Updated 2 weeks ago
• SciML / IRKGaussLegendre.jl
  Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)
  ☆23Updated 2 weeks ago
• aced-differentiate / EquivariantOperators.jl
  ☆19Updated last year