Alternatives and similar repositories for neural-ode

Users that are interested in neural-ode are comparing it to the libraries listed below

• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆56Updated 4 years ago
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆107Updated 4 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• titu1994 / pytorch_odegan
  Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equa…
  ☆16Updated 4 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆119Updated 2 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆47Updated last year
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• isl-org / LMRS
  Source code for ICLR 2020 paper: "Learning to Guide Random Search"
  ☆40Updated 10 months ago
• mandubian / neural-ode
  Neural Ordinary Differential Equation
  ☆101Updated 6 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 5 years ago
• jason71995 / Keras_ODENet
  Implementation of (2018) Neural Ordinary Differential Equations on Keras
  ☆65Updated 6 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• mabirck / adaptative-dropout-pytorch
  Pytorch implementation of Adaptative Dropout a.ka Standout.
  ☆12Updated 7 years ago
• Rachnog / disentanglment
  Experiments with beta-VAE to learn disentangled representations from the data
  ☆65Updated 6 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆90Updated 3 years ago
• uber-research / metropolis-hastings-gans
  ☆116Updated last year
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆33Updated 3 years ago
• aditya-grover / uae
  Uncertainty Autoencoders, AISTATS 2019
  ☆55Updated 6 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆44Updated 6 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆14Updated 6 years ago
• ml-research / pau
  Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network
  ☆63Updated 4 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 6 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 6 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 2 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• AdamCobb / LCBNN
  ☆25Updated 2 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago