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backprop_kf_vo

Implementation of backprop kf (Haarnoja, et al) using PyTorch for visual odometry

backprop_kf_vo-1

Backprop KF with KITTI dataset

brownianmotionmanifold

ceres-solver

A large scale non-linear optimization library

controlledsmc

MATLAB code implementing controlled sequential Monte Carlo methods

cplusplus-_implementation_of_introduction_to_algorithms

《算法导论》第三版中算法的C++实现

crossmodal_filtering1

deephpms

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

differentiablefivo

Working Folder

distributedparticelfilter

A distributed particle filter for a network of agents that are able to measure the distance between them. Each agent keeps a particle set as a representation of the probability distribution, that represent its current belief about its position. A particle set is a set of weighted positions. Can be used for anchourless cooperative localization tasks. Refer to http://robots.stanford.edu/papers/thrun.robust-mcl.pdf for getting an idea of the concept of particle filters. This project is an extension to MCL

dualsmc

dvbf

Python implementation of Deep Variational Bayes Filters introduced by Karl et al.

dvbf.jl

Deep variational Bayes filter in julia using Flux

essentialmath

euclideanizing_flows

Stable dynamical system learning using Euclideanizing flows

fannypack

Tools for training PyTorch models

fbsnns

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

filterflow

gsw

housenavagent

Navigation agent with Bayesian relational memory in the House3D environment

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

kvae

Kalman Variational Auto-Encoder

matlab_demos

it contains all the MATLAB demo code associated with my machine learning notes

motionplanning

Course project for CSE571 (Probabilistic Robotics). Implement Differentiable Particles Filter, Motion Planning Networks and DDPG for a complete navigation pipeline.

multimodalfilter

Code for our IROS 2020 paper

nasmc

An implementation of Neural Adaptive Sequential Monte Carlo (NASMC) using PyTorch

normalizing-flows

An implementation of variational normalizing flows using TF2

normalizing-flows-1

Implementation of normalizing flows in TensorFlow 2 including a small tutorial.

normalizing-flows-2

Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.

paper_notes

This will contain my notes for research papers that I read.