There are 4 repositories under state-space-models topic.
Code Repository for Liquid Time-Constant Networks (LTCs)
Reading list for research topics in state-space models
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
Mambular is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.
R code for Time Series Analysis and Its Applications, Ed 4
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
R package to accompany Time Series Analysis and Its Applications: With R Examples -and- Time Series: A Data Analysis Approach Using R
[CVPR'24 Spotlight] The official implementation of "State Space Models for Event Cameras"
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
Package implementing common state-space routines.
[ACM MM'24 Oral] RainMamba: Enhanced Locality Learning with State Space Models for Video Deraining
The official codebase of the paper "Chemical language modeling with structured state space sequence models"
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
Official implementation of our ECCV paper "StretchBEV: Stretching Future Instance Prediction Spatially and Temporally"
List of papers related to State Space Models (Mamba) in Vision.
[NeurIPS 2024] Official implementation of the paper "MambaLRP: Explaining Selective State Space Sequence Models".
Official repository for Mamba-based Segmentation Model for Speaker Diarization
A toolkit for developing foundation models using Electronic Health Record (EHR) data.
Official Pytorch implementation of NeuralWalker
Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising
Awesome Mamba Papers: A Curated Collection of Research Papers , Tutorials & Blogs
Official implementation of MambaRoll: A Physics-Driven Autoregressive State Space Model for Medical Image Reconstruction (https://arxiv.org/abs/2412.09331)
Gradient-informed particle MCMC methods
Simulates the dynamics of a Reaction Wheel Inverted Pendulum with python.
Julia package for simulating and estimating multi-level/hierarchical dynamic factor models (HDFMs).
Second-order iterated smoothing algorithms for state estimation
Variational Filtering via Wasserstein Gradient Flow
Official implementation of the CBF-SSM model
Accompanying notebook guides for the deep signal processing notes [TBA].