Alternatives and similar repositories for ICSC-HMM:

Users that are interested in ICSC-HMM are comparing it to the libraries listed below

• sorooshafiee / WKF
  ☆14Updated 6 years ago
• young-j-park / 18-NeurIPS-APIAE
  ☆21Updated 6 years ago
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 2 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆51Updated 6 years ago
• danilkuzin / GP-EnKF
  Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…
  ☆17Updated 6 years ago
• BatyaGG / Gaussian-Mixture-Models
  Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR) implemented purely on numpy
  ☆65Updated 6 years ago
• martinseilair / learningoptimalcontrol
  Great resources for learning optimal control
  ☆17Updated 5 years ago
• DiegoAE / BOSD
  ☆25Updated 4 years ago
• zhd96 / ds-hdp-hmm
  Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
  ☆28Updated 4 years ago
• michaelchughes / NPBayesHMM
  Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…
  ☆78Updated 7 years ago
• LCAS / RKN
  ☆47Updated 2 years ago
• Yusufma03 / pfrnns
  Particle Filter Recurrent Neural Networks (AAAI 2020)
  ☆76Updated 9 months ago
• jacobnzw / SSMToybox
  Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature
  ☆13Updated 3 years ago
• zhenwendai / RGP
  Python library for Recurrent Gaussian Processes
  ☆19Updated 7 years ago
• Stanford-ILIAD / active-preference-based-gpr
  Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"
  ☆40Updated last year
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆59Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• rsnirwan / GPLVMsInFinance
  Applications of Gaussian Process Latent Variable Models in Finance
  ☆11Updated 2 years ago
• likang7 / variational-dpgmm
  Variational Dirichlet Process Gaussian Mixture Models
  ☆29Updated 10 years ago
• pmorenoz / RecyclableGP
  Recyclable Gaussian Processes
  ☆11Updated 2 years ago
• davidsandberg / rl_ssms
  State Space Models for Reinforcement Learning in Tensorflow
  ☆19Updated 6 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• Mogeng / IOHMM
  Input Output Hidden Markov Model (IOHMM) in Python
  ☆165Updated 10 months ago
• linesd / SSGPR
  Sparse Spectrum Gaussian Process Regression
  ☆22Updated 5 years ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆32Updated 4 years ago
• hanyas / sds
  A toolbox for inference of switching systems for control
  ☆13Updated 3 years ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago
• resibots / kaushik_2018_multi-dex
  Source code for "Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards" (CoRL 2018)
  ☆13Updated 6 years ago
• GalaxyFox / DS-GA-3001-Deep_Kalman_Filter
  This is a re-implementation and test on paper Deep Kalman Filter: https://arxiv.org/pdf/1511.05121.pdf
  ☆17Updated 5 years ago
• epfl-lasa / ML_toolbox
  A Machine learning toolbox containing algorithms for non-linear dimensionality reduction, clustering, classification and regression along…
  ☆99Updated 4 years ago