Alternatives and similar repositories for STIMD

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

• gatsby-sahani / gp-sde
  ☆15Updated 2 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆50Updated 2 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 7 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 11 months ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• snagcliffs / RKNN
  ☆21Updated 7 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆45Updated 7 years ago
• williamgilpin / fnn
  Embed strange attractors using a regularizer for autoencoders
  ☆135Updated 4 years ago
• anfelopera / lineqGPR
  Gaussian processes regression models with linear inequality constraints
  ☆15Updated last year
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• jamesross2 / Bayesian-HMM
  A non-parametric Bayesian approach to Hidden Markov Models
  ☆86Updated 2 years ago
• pvlachas / RNN-RC-Chaos
  RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…
  ☆97Updated 2 years ago
• n-takeishi / bayesiandmd
  Bayesian Dynamic Mode Decomposition (Bayesian DMD)
  ☆18Updated 3 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆25Updated 10 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• pmorenoz / HierCPD
  Hierarchical Change-Point Detection
  ☆14Updated 7 years ago
• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆34Updated 8 years ago
• kpchamp / MultiscaleDiscovery
  ☆30Updated 7 years ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆138Updated 4 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 3 years ago
• arbabiha / StochasticModelingwData
  Data-driven modeling of chaotic systems in the form of SDEs and nonlinear observation maps
  ☆19Updated 5 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆25Updated last year
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 3 years ago
• Bayes-Works / OpenBDLM
  Bayesian Dynamic Linear Models for time-series analysis
  ☆27Updated 3 years ago
• AaltoML / spatio-temporal-GPs
  Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'
  ☆47Updated 4 years ago
• kormilitzin / the-signature-method-in-machine-learning
  Foundations and Applications
  ☆101Updated 5 years ago