replay-trajectory-classification
State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data
simStateSpace
Provides a streamlined and user-friendly framework for simulating data in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010).
zigma
A PyTorch implementation of the paper "ZigMa: A DiT-Style Mamba-based Diffusion Model" (ECCV 2024)
ncdssm
PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series".
https://github.com/computationalpsychiatry/pyhgf
PyHGF: A neural network library for predictive coding
unsupervised-multimodal-trajectory-modeling
We use EM for a mixture of state space models to perform unsupervised clustering of short trajectories.
bootStateSpace
Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer tto Chow, Ho, Hamaker, and Dolan (2010).