importance-sampling
There are 76 repositories under importance-sampling topic.
nvpro-samples/vk_raytrace
Ray tracing glTF scene with Vulkan
adapt-python/adapt
Awesome Domain Adaptation Python Toolbox
Stonesjtu/Pytorch-NCE
The Noise Contrastive Estimation for softmax output written in Pytorch
banditml/offline-policy-evaluation
Implementations and examples of common offline policy evaluation methods in Python.
nvpro-samples/vk_gltf_renderer
Rendering glTF scenes with ray tracer and raster (Vulkan)
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.
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)
mollnn/manifold-path-guiding
Code for SIGGRAPH Asia 2023 (ToG) paper "Manifold Path Guiding for Importance Sampling Specular Chains"
enkimute/webgl2_pathtrace
:camera: webGL2 path tracing experiment.
dnbaker/minicore
Fast and memory-efficient clustering + coreset construction, including fast distance kernels for Bregman and f-divergences.
ethanleau/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),
alanjian85/prisma
A GPU-accelerated offline PBR path tracer that can generate photorealistic images from glTF scene descriptions using techniques such as microfacet-based BSDF models, BVH & SAH, IS, among others.
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
Jacks0nJ/PyFPT
Stochastic first-passage time (FPT) simulations using importance sampling.
tlienart/EPBP
Expectation Particle Belief Propagation code
vformanyuk/reinforcement-learning
Collection of reinforcement learning algorithms implementations with TensorFlow2
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
leowyy/mcmc-importance-sampling
Markov Chain Monte Carlo (MCMC) and importance sampling in the context of Bayesian linear regression
baturaysaglam/AC-Off-POC
Off-Policy Correction for Actor-Critic Algorithms in Deep Reinforcement Learning
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.
liziniu/ISWBC
Code for NeurIPS 2023 Paper (Imitation Learning from Imperfection: Theoretical Justifications and Algorithms)
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
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.
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.
spock-the-wizard/shapeAdaptiveIR
Code for paper "Inverse Rendering of Translucent Objects using Shape-adaptive Importance Sampling" (PG 2024)
vsimkus/vae-conditional-sampling
[TMLR] Research code for the paper "Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling".