Alternatives and similar repositories for online-neural-cdes:

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

• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆46Updated last year
• YoungseogChung / calibrated-quantile-uq
  Training quantile models
  ☆43Updated 5 months ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆114Updated last year
• ahmedmalaa / Fourier-flows
  ☆18Updated 3 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆115Updated 3 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• abdulfatir / REDSDS
  Pytorch implementation of RED-SDS (NeurIPS 2021).
  ☆18Updated 3 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆59Updated 4 years ago
• mbilos / tsdiff
  ☆14Updated last year
• HerreraKrachTeichmann / NJODE
  code for "Neural Jump Ordinary Differential Equations"
  ☆29Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 6 months ago
• tailintalent / causal
  Discovering directional relations via minimum predictive information regularization
  ☆23Updated 5 years ago
• DiffEqML / tutorials
  ☆10Updated 3 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆74Updated 5 months ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• erichson / LipschitzRNN
  Lipschitz Recurrent Neural Networks
  ☆28Updated 3 years ago
• networkslab / rnn_flow
  ☆23Updated 3 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• tdmeeste / TimeAwareRNN
  Code used for the AAAI 2020 paper "System Identification with Time-Aware Neural Sequence Models"
  ☆17Updated 5 years ago
• edebrouwer / sporadic_ccm
  Pytorch implementation of "Inferring Causal Dependencies between Chaotic Dynamical Systems from Sporadic Time Series"
  ☆9Updated 4 years ago
• boschresearch / Continuous-Recurrent-Units
  ☆64Updated last year
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated 9 months ago
• clear-nus / NCDSSM
  PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularl…
  ☆25Updated last year
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• philipdarke / torchtime
  Benchmark time series data sets for PyTorch
  ☆35Updated last year
• fteufel / PyTorch-GRU-D
  PyTorch Implementation of GRU-D from "Recurrent Neural Networks for Multivariate Time Series with Missing Values" https://arxiv.org/abs/1…
  ☆26Updated 5 years ago
• datasig-ac-uk / signature_applications
  Example applications of path signatures
  ☆38Updated 3 weeks ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆94Updated 3 years ago