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
  ☆74Updated 3 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆118Updated 4 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆118Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆60Updated 11 months ago
• tk-rusch / coRNN
  Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)
  ☆48Updated 4 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆97Updated 3 years ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated 2 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…
  ☆104Updated 3 years ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated last year
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆43Updated 9 months ago
• DiffEqML / tutorials
  ☆10Updated 3 years ago
• patrick-kidger / generalised_shapelets
  Code for "Generalised Interpretable Shapelets for Irregular Time Series"
  ☆57Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 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
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆34Updated 3 years ago
• networkslab / rnn_flow
  ☆23Updated 4 years ago
• Lingkai-Kong / SDE-Net
  Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
  ☆114Updated 4 years ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆97Updated 5 months ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• ahmedmalaa / Fourier-flows
  ☆18Updated 3 years ago
• tk-rusch / unicornn
  Official code for UnICORNN (ICML 2021)
  ☆28Updated 3 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆75Updated 10 months ago
• philipdarke / torchtime
  Benchmark time series data sets for PyTorch
  ☆36Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• tdmeeste / TimeAwareRNN
  Code used for the AAAI 2020 paper "System Identification with Time-Aware Neural Sequence Models"
  ☆17Updated 5 years 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 2 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆129Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 3 months ago
• erichson / LipschitzRNN
  Lipschitz Recurrent Neural Networks
  ☆29Updated 4 years ago
• juliagusak / neural-ode-metasolver
  Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
  ☆25Updated 4 years ago