approximate-inference

FranxYao/Deep-Generative-Models-for-Natural-Language-Processing

DGMs for NLP. A roadmap.

JuliaGaussianProcesses/Stheno.jl

Probabilistic Programming with Gaussian processes in Julia

joennlae/halutmatmul

Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator

Phylliade/awesome-machine-learning-robotics

A curated list of resources about Machine Learning for Robotics

akosiorek/sqair

Implementation of Sequential Attend, Infer, Repeat (SQAIR)

dflemin3/approxposterior

A Python package for approximate Bayesian inference and optimization using Gaussian processes

YingzhenLi/Dropout_BBalpha

Implementations of the ICML 2017 paper (with Yarin Gal)

konstantinos-p/Bayesian-Neural-Networks-Reading-List

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"

JoeMWatson/input-inference-for-control

Input Inference for Control (i2c), a control-as-inference framework for optimal control

ermongroup/SPN_Variational_Inference

PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020

compops/gpo-smc-abc

Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods

ocramz/bayesian-inference

Sheev13/bnn-mean-field-vi

tkusmierczyk/lcvi

Variational Bayesian decision-making for continuous utilities

lacerbi/infbench

Benchmark of posterior and model inference algorithms for (moderately) expensive likelihoods.

ztanml/arLMM

Approximate Ridge Linear Mixed Models (arLMM)

parthnatekar/Loopy-Belief-Propagation

An implementation of loopy belief propagation for binary image denoising. Both sequential and parallel updates are implemented.

Sheev13/bayesian-inference

tmgrgg/localvsglobaluncertainty

Empirical analysis of recent stochastic gradient methods for approximate inference in Bayesian deep learning, including SWA-Gaussian, MultiSWAG, and deep ensembles. See report_localglobal.pdf.

Af4rinz/stot

STOT: Single-Target Object Tracking using particle and Kalman filters [with a bonus multi-target].

dirmeier/ssnl

Simulation-based inference using SSNL

lpcinelli/probabilistic-nn

Probabilistic approach to neural nets - modern scalable approximate inference methods

sanjeevg15/loopy-bp-denoise

Denoise a given image using Loopy Belief Propagation

tkusmierczyk/correcting_approximate_bayesian_predictions

Correcting predictions for approximate Bayesian inference

chrise592/probabilistic_propositions

ErfanXH/Sampling

Implementation of Prior, Rejection, Likelihood and Gibbs Sampling

jswu18/approximate-inference

Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression

rafaol/active-learning-conditional-mean-embeddings

Code repository for the UAI 2020 paper "Active learning of conditional mean embeddings via Bayesian optimisation" by S. R. Chowdhury, R. Oliveira and F. Ramos.

rafaol/no-regret-approximate-inference-via-bo

Code repository for the paper No-Regret Approximate Inference via Bayesian Optimisation, published at UAI 2021

riccmon/Employee-Attrition

FAIKR MOD3 project

zimmerman-cole/hons-proj-public

My undergraduate honours project, with others' private information/code removed.

AaltoML/improved-hyperparameter-learning

Codes for 'Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models' (ICML 2023)

elmahsieh/BayeisanNetworkInference

This project implements both exact and approximate inference techniques for Bayesian Networks using enumeration and rejection sampling, respectively. It processes Bayesian Network structures in XMLBIF format, accepting command-line inputs to compute the posterior distribution of a query variable given observed evidence.