Tree-structured recurrent switching linear dynamical systems
☆39Jul 13, 2020Updated 6 years ago
Alternatives and similar repositories for tree_structured_rslds
Users that are interested in tree_structured_rslds are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Recurrent Switching Linear Dynamical Systems☆129Apr 30, 2023Updated 3 years ago
- Exercises and examples for the latent dynamics workshop☆20Jul 16, 2026Updated 2 months ago
- ☆99Jun 28, 2018Updated 8 years ago
- Bayesian learning and inference for state space models☆724May 9, 2025Updated last year
- Functional matrix factorization via Bayesian tensor filtering☆13Oct 1, 2025Updated last year
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- ☆31Mar 10, 2020Updated 6 years ago
- A toolbox for inference of switching systems for control☆11Aug 23, 2021Updated 5 years ago
- ☆13Nov 3, 2021Updated 4 years ago
- Pseudo-Marginal Slice Sampling☆19Jun 8, 2016Updated 10 years ago
- Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics☆13Feb 23, 2026Updated 7 months ago
- ☆12May 12, 2025Updated last year
- Turning Python into a probabilistic programming language☆19Sep 2, 2014Updated 12 years ago
- Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains☆72Jul 18, 2023Updated 3 years ago
- "Parameter origami" -- folding and unfolding collections of parameters for optimization and sensitivity analysis.☆14Jan 23, 2024Updated 2 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Apr 19, 2016Updated 10 years ago
- Code for fitting neural spike trains with nonparametric hidden Markov and semi-Markov models built upon mattjj's PyHSMM framework.☆16Aug 10, 2018Updated 8 years ago
- Example code for reading SpikeGLX metadata and binary files☆16Jun 24, 2026Updated 3 months ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Jul 10, 2018Updated 8 years ago
- Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation☆61Jan 7, 2021Updated 5 years ago
- changepoint detection for Bayesian models☆19Nov 7, 2014Updated 11 years ago
- ☆80Sep 4, 2021Updated 5 years ago
- A Python package for probabilistic state space modeling with JAX☆1,018Updated this week
- Unifying probabilistic models for time-frequency analysis. Spectral Mixture Gaussian processes in state space form.☆19May 30, 2019Updated 7 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.☆394May 28, 2021Updated 5 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆16Jul 9, 2018Updated 8 years ago
- Stabilizable Nonlinear Dynamics Learning☆22Oct 10, 2019Updated 7 years ago
- some tools for gaussian linear dynamical systems☆90May 14, 2018Updated 8 years ago
- The up-to-date code for Mesoscale Individualized NeuroDynamic modeling and filtering☆12Jul 22, 2021Updated 5 years ago
- Variational Gaussian Process State-Space Models☆25Nov 10, 2015Updated 10 years ago
- Python code for SGMCMC for Time Series SSMs☆16Apr 21, 2021Updated 5 years ago
- a package to support with the statistical analysis of trajectory data☆11Feb 2, 2026Updated 8 months ago
- ☆30Feb 11, 2022Updated 4 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Apr 1, 2019Updated 7 years ago
- code for the paper, "flexible multitask computation in recurrent networks utilizes shared dynamical motifs"☆13Mar 2, 2025Updated last year
- General purpose toolkit for Python☆11Jan 27, 2024Updated 2 years ago
- Pytorch implementation of lfads, and hierarchical extension☆26Dec 2, 2021Updated 4 years ago
- Code for reproducing experiments in Model-Based Active Exploration, ICML 2019☆81Jul 23, 2019Updated 7 years ago
- PyTorch Implementation of Variational Recurrent Autoencoder☆12Sep 10, 2018Updated 8 years ago
- Automated cell tracking package for MATLAB☆11Feb 21, 2019Updated 7 years ago