Alternatives and similar repositories for Variational_Integrator_Networks

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

• mfinzi / constrained-hamiltonian-neural-networks
  ☆110Updated 4 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆35Updated 3 years ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆49Updated 2 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆54Updated last year
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆50Updated last year
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆36Updated 2 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• JSC370 / jsc370.github.io
  Course Website
  ☆9Updated 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
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 3 years ago
• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆43Updated last year
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• greydanus / optimize_wing
  We simulate a wind tunnel, place a rectangular occlusion in it, and then use gradient descent to turn the occlusion into a wing.
  ☆26Updated 4 years ago
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆29Updated 6 months ago
• MJHutchinson / ExtrinsicGaugeIndependentVectorGPs
  A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes
  ☆25Updated 3 years ago
• mbilos / stribor
  Library for normalizing flows and neural flows.
  ☆25Updated 3 years ago
• wzhi / ODElearning_INN
  [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
  ☆10Updated 2 years ago
• libeanim / contact-symplectic-integrator-network
  Contact-Aware Symplectic Integrator Network
  ☆14Updated 2 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆52Updated 3 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…
  ☆69Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• lollcat / fab-torch
  Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.
  ☆58Updated last year
• willieneis / bayesian-algorithm-execution
  Bayesian algorithm execution (BAX)
  ☆50Updated 3 years ago
• DecodEPFL / HamiltonianNet
  PyTorch implementation of Hamiltonian deep neural networks.
  ☆20Updated 3 years ago