Alternatives and similar repositories for Probabilistic-Artificial-Intelligence-ETH

Users that are interested in Probabilistic-Artificial-Intelligence-ETH are comparing it to the libraries listed below

• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆39Updated 5 years ago
• Ulti-Dreisteine / gaussian-process-regression
  高斯过程回归
  ☆78Updated 2 years ago
• aidanscannell / mogpe
  Mixtures of Gaussian Process Experts in GPflow/TensorFlow
  ☆11Updated 2 years ago
• MarcoTodescato / Efficient-GP-Regression-via-Kalman-Filtering
  Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the tempora…
  ☆39Updated 6 years ago
• Bigpig4396 / Incremental-Gaussian-Process-Regression-IGPR
  ☆15Updated 3 years ago
• morim3 / DeepKalmanFilter
  Pytorch Implementation of Deep Kalman Filter
  ☆9Updated 2 years ago
• sorooshafiee / WKF
  ☆15Updated 6 years ago
• Stanford-ILIAD / active-preference-based-gpr
  Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"
  ☆39Updated last year
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• srp98 / Prediction-using-Bayesian-Neural-Network
  Prediction of continuous signals data and Web tracking data using dynamic Bayesian neural network. Compared with other network architectu…
  ☆41Updated 6 years ago
• coursekevin / svise
  Accompanying code for "State Estimation of a Physical System without Governing Equations"
  ☆86Updated 10 months ago
• AlexTMallen / dpk
  Deep Probabilistic Koopman: long-term time-series forecasting under quasi-periodic uncertainty
  ☆23Updated 3 years ago
• iqiukp / Gaussian-Process-Regression
  Gaussian Process Regression using GPML toolbox
  ☆35Updated 5 years ago
• mengcz13 / IJCAI2022_ST-KMRN
  Official implementation of "Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data".
  ☆10Updated 2 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆30Updated 2 years ago
• Magica-Chen / gptp_multi_output
  multivariate Gaussian process regression and multivariate Student-t process regression
  ☆73Updated 3 years ago
• wearepal / UniversalGP
  Generic implementation of GP model
  ☆8Updated 6 years ago
• VBayesLab / VBLab
  Official documentation
  ☆29Updated 4 years ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆91Updated 3 years ago
• Jiacheng-Zhu-AIML / Neural-Processes
  This repository contains PyTorch implementations of Neural Process, Attentive Neural Process, and Recurrent Attentive Neural Process.
  ☆19Updated 4 years ago
• DanieleGammelli / DeepKalmanFilter
  Pyro/Pytorch implementation of Deep Kalman FIlter for shared-mobility demand prediction
  ☆45Updated 5 years ago
• linesd / SSGPR
  Sparse Spectrum Gaussian Process Regression
  ☆23Updated 5 years ago
• zhd96 / ds-hdp-hmm
  Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
  ☆29Updated 4 years ago
• frank0532 / Bayesian_Neural_Networks
  implement bayesian neural networks on tensorflow.
  ☆17Updated 5 years ago
• mlpotter / DeepKoopmanLusch
  PyTorch Implementation of Lusch et al DeepKoopman
  ☆13Updated 2 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆65Updated 2 years ago
• Weizhe-Chen / OSGPR
  GPyTorch Implementation of Online Sparse Gaussian Process Regression
  ☆10Updated last year
• 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
• panweihit / BSID
  Bayesian System IDentification
  ☆28Updated 7 years ago
• NicolasDurrande / Gaussian-Process-Regression-handout
  ☆39Updated 8 years ago