Alternatives and similar repositories for neuralRDEs:

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

• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆113Updated last year
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 2 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated 10 months ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• patrick-kidger / Deep-Signature-Transforms
  Code for "Deep Signature Transforms" (NeurIPS 2019)
  ☆93Updated 8 months ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• g-benton / Volt
  Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
  ☆48Updated 2 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆54Updated 4 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 3 years ago
• gerdm / bayes
  Neat Bayesian machine learning examples
  ☆55Updated 2 months ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆123Updated 3 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆46Updated last year
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 6 months ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆74Updated 4 months ago
• samcohen16 / Aligning-Time-Series
  ☆51Updated 8 months ago
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆103Updated 4 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆46Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated last year
• cunningham-lab / cb_and_cc
  ☆36Updated 2 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• siboehm / NormalizingFlowNetwork
  Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982
  ☆21Updated 4 years ago
• TyXe-BDL / TyXe
  ☆151Updated 2 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆53Updated 10 months ago
• tk-rusch / unicornn
  Official code for UnICORNN (ICML 2021)
  ☆27Updated 3 years ago