Alternatives and similar repositories for ODElearning_INN:

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

• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆42Updated last year
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• steindoringi / Variational_Integrator_Networks
  ☆18Updated 2 years ago
• MJHutchinson / ExtrinsicGaugeIndependentVectorGPs
  A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes
  ☆25Updated 3 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated 11 months ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆34Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• IvanYashchuk / jax-fenics
  Differentiable interface to FEniCS for JAX
  ☆52Updated 3 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆28Updated 2 weeks ago
• dimitra-maoutsa / DeterministicParticleFlowControl
  Repository for Deterministic Particle Flow Control framework
  ☆10Updated 2 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• dimitra-maoutsa / odes_for_sdes
  Deterministic particle dynamics for simulating Fokker-Planck probability flows
  ☆24Updated last year
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆36Updated 2 years ago
• ivandariojr / LyapunovLearning
  ☆39Updated last year
• gd-vae / gd-vae
  Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This …
  ☆25Updated last year
• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆32Updated 2 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆18Updated last year
• mfinzi / residual-pathway-priors
  ☆18Updated 3 years ago
• danieljtait / ladax
  Layered distributions using FLAX/JAX
  ☆10Updated 4 years ago
• IPL-UV / jaxkern
  A lightweight didactic library of kernel methods using the back-end JAX.
  ☆12Updated last year
• lorenzrichter / PDE-backward-solver
  ☆20Updated 3 months ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆47Updated 2 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆69Updated 4 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.
  ☆25Updated 4 years ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆43Updated last year
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆11Updated last year
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago