Alternatives and similar repositories for torchdiffeq:

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

• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆57Updated 5 months ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆113Updated last year
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• facebookresearch / neural_stpp
  Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…
  ☆101Updated 3 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆94Updated 3 years ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆84Updated 4 years ago
• babylonhealth / neuralTPPs
  ☆29Updated last year
• HerreraKrachTeichmann / NJODE
  code for "Neural Jump Ordinary Differential Equations"
  ☆29Updated 2 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆46Updated last year
• ChengzijunAixiaoli / PPMM
  Python3 implementation of the paper [Large-scale optimal transport map estimation using projection pursuit]
  ☆16Updated 4 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆60Updated 4 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆126Updated 6 months ago
• abdulfatir / REDSDS
  Pytorch implementation of RED-SDS (NeurIPS 2021).
  ☆18Updated 3 years ago
• networkslab / rnn_flow
  ☆23Updated 3 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆53Updated 9 months ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆14Updated 9 months ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆116Updated 3 years ago
• pamattei / miwae
  Implementation of the MIWAE method for deep generative modelling of incomplete data sets.
  ☆37Updated last year
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• Zymrael / gde
  Neural Graph Differential Equations (Neural GDEs)
  ☆200Updated 3 years ago
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated last year