nbfigueroa / ICSC-HMMLinks
Toolbox for IBP Coupled SPCM-CRP Hidden Markov Model. Also contains code for EM-based HMM learning and inference for Bayesian non-parametric HDP-HMM and IBP-HMM.
☆14Updated 6 years ago
Alternatives and similar repositories for ICSC-HMM
Users that are interested in ICSC-HMM are comparing it to the libraries listed below
Sorting:
- Python implementation of the PR-SSM.☆56Updated 7 years ago
- ☆21Updated 6 years ago
- ☆16Updated 7 years ago
- Continual Gaussian Processes☆31Updated 2 years ago
- ☆26Updated 5 years ago
- ☆46Updated 3 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR) implemented purely on numpy☆72Updated 6 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 7 years ago
- Python library for Recurrent Gaussian Processes☆20Updated 8 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆22Updated 4 years ago
- 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
- Great resources for learning optimal control☆18Updated 6 years ago
- This is a re-implementation and test on paper Deep Kalman Filter: https://arxiv.org/pdf/1511.05121.pdf☆19Updated 5 years ago
- Gaussian Mixture Regression☆196Updated 2 months ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Applications of Gaussian Process Latent Variable Models in Finance☆11Updated 3 years ago
- Nonlinear Sigma-Point Kalman Filters based on Bayesian Quadrature☆12Updated 4 years ago
- Autoregressive policies for continuous control reinforcement learning☆32Updated 6 years ago
- Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…☆78Updated 7 years ago
- Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.☆98Updated 3 years ago
- Code for VIREL: A Variational Inference Framework for Reinforcement Learning☆14Updated 5 years ago
- Code for training and testing a Hidden Parameter Markov Decision Process, used to facilitate the transfer of learning☆31Updated 7 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- A library of probabilistic model based RL algorithms in pytorch☆107Updated 4 years ago
- Stabilizable Nonlinear Dynamics Learning☆22Updated 6 years ago
- Sparse Spectrum Gaussian Process Regression☆23Updated 5 years ago
- Variational Dirichlet Process Gaussian Mixture Models☆29Updated 10 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Input Output Hidden Markov Model (IOHMM) in Python☆171Updated last year