Alternatives and similar repositories for sigkernel

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

• anh-tong / signax
  Signax: Signature computation in JAX
  ☆29Updated 4 months ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 10 months ago
• datasig-ac-uk / esig
  esig python package
  ☆48Updated 5 months ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆103Updated last year
• datasig-ac-uk / signature_applications
  Example applications of path signatures
  ☆39Updated 2 months ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆12Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆170Updated 3 years ago
• datasig-ac-uk / RoughPy
  Toolbox for working with streaming data as rough paths in Python
  ☆36Updated last week
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆12Updated 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
• yjlolo / pytorch-deep-markov-model
  PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]
  ☆24Updated 4 years ago
• patrick-kidger / Deep-Signature-Transforms
  Code for "Deep Signature Transforms" (NeurIPS 2019)
  ☆93Updated 10 months ago
• Benjamin-Walker / log-neural-cdes
  Code for "Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference" (ICML 2024)
  ☆17Updated last week
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆59Updated 4 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆118Updated 4 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆40Updated 5 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• HHalva / hmnlica
  Code for Hidden Markov Nonlinear ICA
  ☆24Updated 3 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 2 years ago
• g-benton / Volt
  Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
  ☆49Updated 2 years ago
• patrick-kidger / signatory
  Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)
  ☆272Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• TyXe-BDL / TyXe
  ☆153Updated 2 years ago
• andrew-cr / online_var_fil
  Code for our paper: Online Variational Filtering and Parameter Learning
  ☆18Updated 3 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆66Updated 4 months ago