Alternatives and similar repositories for MarkovRNNs:

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

• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated 8 months ago
• KurochkinAlexey / Recurrent-neural-processes
  Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf
  ☆21Updated 5 years ago
• jambo6 / online-neural-cdes
  Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"
  ☆38Updated 2 years ago
• karlnapf / ds3_kernel_testing
  Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"
  ☆26Updated 6 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• sjblim / rnf-ijcnn-2020
  Recurrent Neural Filters for Time Series Prediction
  ☆24Updated 5 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• manuwhs / BayesianRNN
  Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.
  ☆40Updated 7 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 5 years ago
• jmarecek / OnlineLDS
  Source code for the AAAI 2019 paper "On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters" (https://arx…
  ☆19Updated 4 years ago
• alan-turing-institute / rbocpdms
  Robust bayesian online changepoint detection with model selection
  ☆23Updated 6 years ago
• edebrouwer / sporadic_ccm
  Pytorch implementation of "Inferring Causal Dependencies between Chaotic Dynamical Systems from Sporadic Time Series"
  ☆9Updated 4 years ago
• iankurgarg / Reinforcement-Learning-Feature-Selection
  Feature selection for maximizing expected cumulative reward
  ☆30Updated 7 years ago
• yiyuezhuo / Deep-Latent-Gaussian-Models
  PyTorch implementation for Deep Latent Gaussian Models(DLGM) https://arxiv.org/abs/1401.4082
  ☆9Updated 5 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆31Updated 3 years ago
• shz9 / csc2541-ml-project
  Modeling Uncertainty in RNNs for Time Series Forecasting
  ☆14Updated 7 years ago
• steveli / partial-encoder-decoder
  An encoder-decoder framework for learning from incomplete data
  ☆46Updated last year
• crazysal / VariationalRNN
  A Recurrent Latent Variable Model for Sequential Data
  ☆26Updated 6 years ago
• 2M-kotb / LSTM-based-Stacked-Autoencoder
  ☆19Updated 3 years ago
• tailintalent / causal
  Discovering directional relations via minimum predictive information regularization
  ☆23Updated 5 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
• Sarunas-Girdenas / neural_decomposition
  Neural Decomposition Code for Time Series
  ☆21Updated 6 years ago
• nla-group / ABBA-LSTM
  ☆15Updated 2 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆40Updated 2 years ago
• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆50Updated 5 years ago
• dlegor / rad
  Implementation of Robust PCA and Robust Deep Autoencoder over Time Series
  ☆14Updated 4 years ago
• pmorenoz / HierCPD
  Hierarchical Change-Point Detection
  ☆14Updated 6 years ago
• thangbui / deepGP_approxEP
  see https://github.com/thangbui/geepee for a faster implementation
  ☆37Updated 7 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• jsyoon0823 / Clairvoyance
  Codebase for "Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series"
  ☆13Updated 4 years ago