Alternatives and similar repositories for awesome-implicit-neural-models

Users that are interested in awesome-implicit-neural-models are comparing it to the libraries listed below

• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆56Updated 4 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆119Updated last year
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆90Updated 3 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆82Updated 3 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆75Updated 11 months ago
• ebekkers / gsplinets
  B-Spline CNNs on Lie groups
  ☆54Updated 5 years ago
• tensorly / torch
  TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch
  ☆79Updated last year
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆52Updated 5 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆47Updated last year
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 8 months ago
• sbarratt / torch_cg
  Preconditioned Conjugate Gradient in Pytorch
  ☆140Updated last year
• nimadehmamy / L-conv-code
  Lie Algebra Convolutional Network implementation
  ☆43Updated 3 years ago
• liruilong940607 / NeuralODE
  The simplest pytorch implement (100 lines) of "Neural Ordinary Differential Equations" @ NeurIPS 2018 Best Paper.
  ☆78Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• mauriceweiler / MobiusCNNs
  This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of Coordinate Independent…
  ☆72Updated last year
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆52Updated 11 months ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆56Updated 6 years ago
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆90Updated last year
• wgrathwohl / VERA
  ☆63Updated last year
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆104Updated 4 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 6 years ago
• mfinzi / LieConv
  ☆269Updated 2 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆128Updated 9 months ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆281Updated 3 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago