Alternatives and similar repositories for signatory:

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

• patrick-kidger / Deep-Signature-Transforms
  Code for "Deep Signature Transforms" (NeurIPS 2019)
  ☆93Updated 6 months ago
• bottler / iisignature
  Iterated integral signature calculations
  ☆102Updated 3 months ago
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆428Updated last year
• datasig-ac-uk / esig
  esig python package
  ☆44Updated 2 months ago
• patrick-kidger / NeuralCDE
  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
  ☆635Updated 2 years ago
• anh-tong / signax
  Signax: Signature computation in JAX
  ☆26Updated 3 weeks ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆115Updated 3 years ago
• kormilitzin / the-signature-method-in-machine-learning
  Foundations and Applications
  ☆94Updated 4 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆53Updated 9 months ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆46Updated last year
• jambo6 / generalised-signature-method
  Code for: "A Generalised Signature Method for Time Series"
  ☆60Updated last year
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆191Updated last year
• g-benton / Volt
  Public Implementation of Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes
  ☆48Updated 2 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆431Updated 5 months ago
• pafoster / path_signatures_introduction
  A Brief Introduction to Path Signatures for Machine Learning Practitioners
  ☆45Updated 3 years ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆222Updated 2 months ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆275Updated 3 years ago
• YuliaRubanova / latent_ode
  Code for "Latent ODEs for Irregularly-Sampled Time Series" paper
  ☆542Updated 4 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆113Updated last year
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆232Updated last year
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆201Updated 3 months ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆229Updated 4 years ago
• edebrouwer / gru_ode_bayes
  Pytorch implementation of GRU-ODE-Bayes
  ☆228Updated 2 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆124Updated 4 months ago
• probml / sts-jax
  Structural Time Series in JAX
  ☆187Updated 9 months ago
• facebookincubator / flowtorch
  This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…
  ☆306Updated 2 months ago
• izmailovpavel / understandingbdl
  ☆236Updated 2 years ago
• gpapamak / maf
  Masked Autoregressive Flow
  ☆209Updated 6 months ago
• TyXe-BDL / TyXe
  ☆149Updated 2 years ago