PointMamba: A Simple State Space Model for Point Cloud Analysis
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Updated
Jun 13, 2024 - Python
PointMamba: A Simple State Space Model for Point Cloud Analysis
PyHGF: A neural network library for predictive coding
A PyTorch implementation of the paper "ZigMa: A DiT-Style Mamba-based Diffusion Model"
Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models, KDD 2023
Neural State-Space Models and Latent Dynamics Functions in PyTorch for High-Dimensional Forecasting
Accelerated First Order Parallel Associative Scan
[IEEE TGRS 2024] ChangeMamba: Remote Sensing Change Detection Based on Spatio-Temporal State Space Model
Official Implementation of the work "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning"
This repository contains the source code for "Stochastic data-driven model predictive control using Gaussian processes" (SDD-GP-MPC).
State space models for categorization of replay content from multiunit spiking activity. Deng et al. 2016
Official PyTorch implementation of the CVPR 2024 paper: State Space Models for Event Cameras (Spotlight).
Newton-based maximum likelihood estimation in nonlinear state space models
Variational Joint Filtering
An official implementation for SSAMBA: Self-Supervised Audio Mamba
We use EM for a mixture of state space models to perform unsupervised clustering of short trajectories.
A flexible data simulator for Kafka and OpenShift using state-space models
Conrol theory project a friend and I did for our Intelligent Control class during our minor (undergraduate level)
Python state-space models
PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series".
Arbitrage-free Dynamic Generalized Nelson-Siegel model of interest rates following Christensen, Diebold and Rudebusch; and its estimation using the Kalman filter / maximum likelihood.
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