Alternatives and similar repositories for DeepKalmanFilter

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

• 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
  ☆19Updated 5 years ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆96Updated 3 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 7 years ago
• Yusufma03 / pfrnns
  Particle Filter Recurrent Neural Networks (AAAI 2020)
  ☆79Updated 11 months ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆45Updated 2 years ago
• LCAS / RKN
  ☆46Updated 2 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆30Updated 3 years ago
• linesd / SSGPR
  Sparse Spectrum Gaussian Process Regression
  ☆23Updated 5 years ago
• Bigpig4396 / Incremental-Gaussian-Process-Regression-IGPR
  ☆16Updated 3 years ago
• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆40Updated 6 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆67Updated 2 years ago
• sorooshafiee / WKF
  ☆15Updated 6 years ago
• networkslab / rnn_flow
  ☆23Updated 4 years ago
• jgosmann / goppy
  Gaussian Online Processes for Python
  ☆18Updated 6 months ago
• xuwd11 / Dropout_Tutorial_in_PyTorch
  Dropout as Regularization and Bayesian Approximation
  ☆59Updated 6 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 4 years ago
• jnez71 / kalmaNN
  Extended Kalman filter for training neural-networks
  ☆93Updated 4 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆43Updated 7 months ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated 11 months ago
• pmorenoz / RecyclableGP
  Recyclable Gaussian Processes
  ☆11Updated 2 years ago
• AnthonyRentsch / calibrated_regression
  A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.
  ☆51Updated 5 years ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆95Updated 3 months ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 2 years ago
• k920049 / Deep-Kalman-Filter
  ☆24Updated 7 years ago
• georgosgeorgos / graph-signal-reconstruction
  Signal recovery and sampling over graphs
  ☆16Updated 6 years ago
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆45Updated 4 years ago
• Rose-STL-Lab / ECCO
  ☆54Updated 3 years ago
• ivanalberico / Probabilistic-Artificial-Intelligence-ETH
  Graded projects of the course "Probabilistic Artificial Intelligence", ETH Zürich (Fall 2020). Topics: Gaussian Process Regression, Bayes…
  ☆11Updated 3 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…
  ☆40Updated 7 years ago