An Intuitive tutorial on Bayesian filtering
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Updated
Jul 19, 2024 - Python
An Intuitive tutorial on Bayesian filtering
Official Pytorch repository for "Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective", where FPS (Filtering Posterior Sampling) as well as its extension FPS-SMC are proposed.
Code supplement for "The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models"
Variational Joint Filtering
A Julia package that provides high-level abstractions for simulating and deploying stochastic filters
Code supplement for "Discriminative Bayesian Filtering Lends Momentum to the Stochastic Newton Method for Minimizing Log-Convex Functions"
These slides were presented at my dissertation defense (Division of Applied Mathematics, Brown University, 23 May 2018).
XeLaTeX for "A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding"
This repository contains code implementations for the Discriminative Kalman Filter.
Expected free energy minimization with approximations to nonlinear observation functions
This is a comprehensive project focused on implementing popular algorithms for state estimation, robot localization, 2D mapping, and 2D & 3D SLAM. It utilizes various types of filters, including the Kalman Filter, Extended Kalman Filter, Unscented Kalman Filter, and Particle Filter.
A Kalman filter and Particle Filter implementation for Gaussian object tracking
The workspace for our computational robotics class. I explored different techniques such as Bayesian filtering in a Gridworld environment, Graph Based Motion Planning on a chess board, Kalman Filtering... Work in progress !
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