Alternatives and similar repositories for Neural-Manifold-Ordinary-Differential-Equations

Users that are interested in Neural-Manifold-Ordinary-Differential-Equations are comparing it to the libraries listed below

• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆47Updated last year
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 2 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆56Updated 4 years ago
• pimdh / lie-vae
  VAEs with Lie Group latent space
  ☆99Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆82Updated 4 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆55Updated last year
• massastrello / awesome-implicit-neural-models
  ☆102Updated 4 years ago
• dimkal89 / rvae
  ☆38Updated 5 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• xinshi-chen / ParticleFlowBayesRule
  Pytorch implementation for "Particle Flow Bayes' Rule"
  ☆14Updated 6 years ago
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆107Updated 4 years ago
• mfinzi / LieConv
  ☆272Updated 2 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• akandykeller / SelfNormalizingFlows
  ☆68Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 9 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• geomstats / challenge-iclr-2022
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆51Updated 3 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆230Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• PrincetonLIPS / RandomizedAutomaticDifferentiation
  Experiment code for "Randomized Automatic Differentiation"
  ☆67Updated 5 years ago
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated last year
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆29Updated 5 months ago