sampling-methods

A class-leading water system implemented in Unity

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

Structured Volume Sampling - sample placement algorithm for real-time volume rendering with low aliasing, for camera-in-volume case.

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

a framework for training sequence-level deep learning networks

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

Official implementation for the paper "Model-based Diffusion for Trajectory Optimization". Model-based diffusion (MBD) is a novel diffusion-based trajectory optimization framework that employs a dynamics model to run the reverse denoising process to generate high-quality trajectories.

⚡️ zeus: Lightning Fast MCMC ⚡️

Python toolbox for sampling Determinantal Point Processes

Parametric Voronoi generator with real time editing and SVG export

MCMC sample analysis, kernel densities, plotting, and GUI

PyTorch implementation for "Parallel Sampling of Diffusion Models", NeurIPS 2023 Spotlight

Official implementation for the paper "CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design" accepted by L4DC 2024. CoVO-MPC is an optimal sampling-based MPC algorithm.

Lightweight library of stochastic gradient MCMC algorithms written in JAX.

pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation

Public version of PolyChord: See polychord.co.uk for PolyChordPro

Official Code for "Non-Probability Sampling Network for Stochastic Human Trajectory Prediction (CVPR 2022)"

[ICLR2025] The code of Z-Sampling, proposed in our paper "Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection".

GPU Performance Advisor

Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!