242 Open source projects that are alternatives of or similar to Particles

solution of exercises of the book "probabilistic robotics"

Bayes by Backprop implemented in a CNN in PyTorch

Paper Reading

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

A Bayesian Analysis Toolkit in Julia

Python Kalman filters vectorized as Single Instruction, Multiple Data

This package includes basic tools for time series analysis, compatible with incomplete data.

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

The base NIMBLE package for R

Udacity Self-Driving Car Engineer Nanodegree. Project: Extended Kalman Filters

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

GPstuff - Gaussian process models for Bayesian analysis

Projection predictive variable selection

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Deep Learning over PyTorch

Fast and Easy Infinite Neural Networks in Python

Diffusive Nested Sampling

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C++ template library for probabilistic programming

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PyMC3 educational resources

Code for "A-NICE-MC: Adversarial Training for MCMC"

A Python package for building Bayesian models with TensorFlow or PyTorch

A high-level Bayesian analysis API written in Python

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

Machine learning, in numpy

Pharmaceutical Modeling and Simulation for Nonlinear Mixed Effects (NLME), Quantiative Systems Pharmacology (QsP), Physiologically-Based Pharmacokinetics (PBPK) models mixed with machine learning

Bayesian multi-object tracking

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Multiple Object Tracker, Based on Hungarian algorithm + Kalman filter.

Bayesian inference with probabilistic programming.

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

A method for variant graph genotyping based on exact alignment of k-mers

Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API

BlackJAX is a sampling library designed for ease of use, speed and modularity.

Statistical Rethinking with PyTorch and Pyro

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

A qualitative probabilistic programming language based on ranking theory

A Python library that helps data scientists to infer causation rather than observing correlation.

Generalized linear mixed-effect model in Python

Distributed Bayesian Entity Resolution in Apache Spark

Loosely coupled integration of GNSS and IMU

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

Kalman Variational Auto-Encoder

Deep universal probabilistic programming with Python and PyTorch

Infer.NET is a framework for running Bayesian inference in graphical models

Lightweight Python library for adding real-time 2D object tracking to any detector.

Fast & scalable MCMC for all your exoplanet needs!

A resource list for causality in statistics, data science and physics

Modular Probabilistic Programming on MXNet

Python package for computing the Curie depth from the magnetic anomaly

BOPP: Bayesian Optimization for Probabilistic Programs

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

MrBayes is a program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models. For documentation and downloading the program, please see the home page:

An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

TAPAS - Translational Algorithms for Psychiatry-Advancing Science

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg