Alternatives and similar repositories for StatefulOdeNets:

Users that are interested in StatefulOdeNets are comparing it to the libraries listed below

• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆57Updated 5 months ago
• juntang-zhuang / TorchDiffEqPack
  ☆45Updated last year
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆18Updated last year
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆37Updated 2 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆54Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆49Updated last year
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆105Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆51Updated 7 months 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
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆89Updated 3 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• AlexandraVolokhova / stochasticity_in_neural_ode
  "Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper
  ☆13Updated 4 years ago
• DiffEqML / kairos
  Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure
  ☆24Updated 2 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆82Updated 3 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• devzhk / cgds-package
  Package for CGD and ACGD optimizers
  ☆20Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• lorenzrichter / PDE-backward-solver
  ☆20Updated 5 months ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆19Updated 3 weeks ago
• yuan-yin / LEADS
  Learning Dynamical Systems that Generalize Across Environments
  ☆19Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 6 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 2 years ago