importance-sampling

Stonesjtu/Pytorch-NCE

The Noise Contrastive Estimation for softmax output written in Pytorch

adapt-python/adapt

Awesome Domain Adaptation Python Toolbox

banditml/offline-policy-evaluation

Implementations and examples of common offline policy evaluation methods in Python.

TatevKaren/mathematics-statistics-for-data-science

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

nvpro-samples/vk_shaded_gltfscene

Rendering glTF scenes with ray tracer and raster (Vulkan)

pypmc/pypmc

Clustering with variational Bayes and population Monte Carlo

WayneDW/Contour-Stochastic-Gradient-Langevin-Dynamics

An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)

enkimute/webgl2_pathtrace

:camera: webGL2 path tracing experiment.

mollnn/manifold-path-guiding

Code for SIGGRAPH Asia 2023 (ToG) paper "Manifold Path Guiding for Importance Sampling Specular Chains"

RLOpensource/IMPALA-Scalable-Distributed-Deep-RL-with-Importance-Weighted-Actor-Learner-Architectures

dnbaker/minicore

Fast and memory-efficient clustering + coreset construction, including fast distance kernels for Bregman and f-divergences.

lyfxyz/bisml

Implementation of the paper: Adaptive BRDF-Oriented Multiple Importance Sampling of Many Lights

SiavashMT/OCT-MPS

Massively Parallel Simulator of Optical Coherence Tomography (OCT-MPS)

Lcrypto/trapping-sets-enumeration

Importance Sampling and Linear Programming based Enumerating and Weighing of Trapping sets in LDPC codes, ISING models and related DNN Arch( Transformer, RBM, BM, SPN und etc),

arviz-devs/PSIS.jl

Pareto smoothed importance sampling

lxcnju/sampling

Some methods to sampling data points from a given distribution.

nbip/notMIWAE

Code accompanying the notMIWAE paper

vformanyuk/reinforcement-learning

Collection of reinforcement learning algorithms implementations with TensorFlow2

leowyy/mcmc-importance-sampling

Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression

tlienart/EPBP

Expectation Particle Belief Propagation code

hammouc/Multilevel-Monte-Carlo-with-Importance-Sampling-for-SRNs

This repository includes Matlab codes/routines that were used in our manuscript entitled "Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks" that can be found in this preprint: https://arxiv.org/abs/1911.06286

baturaysaglam/AC-Off-POC

Off-Policy Correction for Actor-Critic Algorithms in Deep Reinforcement Learning

Jacks0nJ/PyFPT

Stochastic first-passage time (FPT) simulations using importance sampling.

kgourgou/adaptive-importance-sampling-BN

Experimental code: adaptive importance sampling for bayesian networks.

bradleyboyuyang/5G-SLA-Simulation

Service level agreement simulation for 5G network based on queueing systems.

Julien6431/Importance-Sampling-VAE

Software and data related to the paper "Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling"

jumboRT/jumboRT

A lightweight, portable and powerful pathtracer

nbip/IWAE

Importance Weighted Autoencoders in TensorFlow 2, reproducing results from the IWAE paper with 1 or 2 stochastic layers

boennecd/pedmod

R package with quasi-Monte Carlo methods to estimate mixed models commonly used for random effect structures from pedigrees.

Davide-Mapelli/Numeric_Simulation_Laboratory

Numerical Simulation Laboratory at Unimi in 2020-2021 (D.E. Galli). Advanced Monte Carlo methods: Markov chains, Metropolis algorithm. Numerical simulations in statistical mechanics. Stochastic calculus and stochastic differential equation. Computational intelligence, stochastic optimization. Parallel computing and parallel programming. Machine learning and deep neural networks

liziniu/ISWBC

Code for NeurIPS 2023 Paper (Imitation Learning from Imperfection: Theoretical Justifications and Algorithms)

alvincjk/sampling-manifold-restricted-gaussians

Sampling from manifold-restricted Gaussians.

draktr/monte-library

Monte is a set of Monte Carlo methods in Python. The package is written to be flexible, clear to understand and encompass variety of Monte Carlo methods.

robinlau1981/MarginalLikelihoodEstimator

Matlab code for the adaptive annealed importance sampling based marginal likelihood estimator.

ZJLAB-AMMI/HS-OMRL

Python code to implement hard sampling based task representation learning for robust offline meta RL