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

python machine-learning bayesian-inference dag causality-analysis structure-learning causal causal-models sampling-methods directed-acyclic-graph causal-networks parameter-learning

Updated Oct 25, 2024
Jupyter Notebook

FunctionLab / selene

Star

a framework for training sequence-level deep learning networks

deep-learning genomic-data-analysis sampling-methods

Updated Sep 30, 2024
Jupyter Notebook

wiseodd / MCMC

Star

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

machine-learning bayesian-inference mcmc markov-chain-monte-carlo sampling-methods

Updated Dec 20, 2017
Python

minaskar / zeus

Star

⚡️ zeus: Lightning Fast MCMC ⚡️

python machine-learning inference sampling bayesian-inference general-purpose mcmc mcmc-sampler sampling-methods probabilistic-data-analysis black-box-bayesian-inference

Updated Feb 18, 2024
Python

guilgautier / DPPy

Star

Python toolbox for sampling Determinantal Point Processes

python sampling-methods random-matrix-theory determinantal-processes determinantal-point-processes

Updated Aug 14, 2024
Python

WebSVG / voronoi

Star

Parametric Voronoi generator with real time editing and SVG export

svg bootstrap vanilla-js static-site svg-filters css-grid client-side voronoi template-string geometric-algorithms sampling-methods

Updated Jul 20, 2024
JavaScript

LeCAR-Lab / model-based-diffusion

Star

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.

control optimization planning rl trajectory-optimization diffusion trajectory sampling-methods diffusion-models zeroth-order-optimization

Updated Oct 19, 2024
Jupyter Notebook

cmbant / getdist

Star

MCMC sample analysis, kernel densities, plotting, and GUI

statistical-inference mcmc kernel-density-estimation sampling-methods contour-plot plotting-in-python

Updated Oct 24, 2024
Python

AndyShih12 / paradigms

Star

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

pytorch sampling-methods diffusion-models stable-diffusion

Updated Oct 13, 2023
Python

LeCAR-Lab / CoVO-MPC

Star

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.

control drone mpc quadrotor sampling-methods zeroth-order-optimization

Updated May 22, 2024
Python

jeremiecoullon / SGMCMCJax

Star

Lightweight library of stochastic gradient MCMC algorithms written in JAX.

bayesian-inference sampling-methods jax

Updated Oct 23, 2023
Python

minaskar / pocomc

Star

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

python machine-learning astronomy inference cosmology astrophysics sampling bayesian-inference smc general-purpose mcmc mcmc-sampler normalizing-flows sampling-methods probabilistic-data-analysis black-box-bayesian-inference cosmology-inference

Updated Oct 30, 2024
Python

PolyChord / PolyChordLite

Star

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

statistics astronomy mpi gfortran cosmology bayesian-inference particle-physics openmpi nested-sampling posterior log-likelihood sampling-methods polychord

Updated Jun 13, 2024
Fortran

IBM / xgboost-smote-detect-fraud

Star

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!