Alternatives and similar repositories for symplectic-adjoint-method:

Users that are interested in symplectic-adjoint-method are comparing it to the libraries listed below

• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆37Updated 2 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• martenlienen / finite-element-networks
  Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…
  ☆70Updated 10 months ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆106Updated 3 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆49Updated last year
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆18Updated last year
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆48Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆71Updated 4 years ago
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆76Updated 3 years ago
• NBoulle / RationalNets
  Code for the paper "Rational neural networks", NeurIPS 2020
  ☆28Updated 4 years ago
• facebookresearch / SparseBO
  code associated with paper "Sparse Bayesian Optimization"
  ☆26Updated last year
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 6 months ago
• samholt / NeuralLaplace
  Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
  ☆75Updated last month
• lbl-camera / fvGP
  A software package for flexible HPC GPs
  ☆16Updated last month
• DiffEqML / kairos
  Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure
  ☆24Updated 2 years ago
• dimitra-maoutsa / odes_for_sdes
  Deterministic particle dynamics for simulating Fokker-Planck probability flows
  ☆24Updated 2 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆21Updated last month
• rdyro / torch2jax
  Wraps PyTorch code in a JIT-compatible way for JAX. Supports automatically defining gradients for reverse-mode AutoDiff.
  ☆48Updated last month
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆51Updated 8 months ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆54Updated 4 years ago
• mbilos / stribor
  Library for normalizing flows and neural flows.
  ☆24Updated 2 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆34Updated 3 years ago
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆116Updated 2 months ago
• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆34Updated 2 years ago
• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆42Updated last year