Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator
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Dec 10, 2023 - Python
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approximate-inference
Here are 15 public repositories matching this topic...
A Python package for approximate Bayesian inference and optimization using Gaussian processes
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Nov 5, 2023 - Python
Implementations of the ICML 2017 paper (with Yarin Gal)
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Dec 15, 2017 - Python
Input Inference for Control (i2c), a control-as-inference framework for optimal control
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Sep 6, 2023 - Python
PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
pytorch graphical-models variational-inference approximate-inference sum-product-networks probabilistic-circuits
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Oct 11, 2021 - Python
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
particle-filter gaussian-processes bayesian-optimization stochastic-volatility-models portfolio-analysis approximate-bayesian-computation approximate-inference gaussian-process-optimisation alpha-stable-processes
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Nov 29, 2017 - Python
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.
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Dec 5, 2021 - Python
An implementation of loopy belief propagation for binary image denoising. Both sequential and parallel updates are implemented.
ising-model probabilistic-graphical-models belief-propagation approximate-inference loopy-belief-propagation loopy-bp
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May 27, 2020 - Python
Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression
variational-bayes approximate-inference loopy-belief-propagation gaussian-process-regression automatic-relevance-determination expectation-maximisation mean-field-approximation
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Jun 13, 2023 - Python
Code for my PhD project on perceptual inference.
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Nov 10, 2025 - Python
A Python implementation of Bayesian Networks from scratch, featuring exact inference (Variable Elimination) and approximate inference algorithms (Rejection Sampling, Gibbs Sampling, and Likelihood Weighting).
python university-project bayesian-network course-project bayesian-inference rejection-sampling probabilistic-graphical-models gibbs-sampling conditional-probability variable-elimination generative-models approximate-inference likelihood-weighting mcmc-sampling
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Oct 30, 2025 - Python
Implementation of Prior, Rejection, Likelihood and Gibbs Sampling
inference sampling rejection-sampling likelihood gibbs-sampling sampling-methods approximate-inference exact-inference prior-sampling
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Feb 4, 2024 - Python
Surjective sequential neural likelihood estimation
bayesian-inference normalizing-flows approximate-inference jax simulation-based-inference surjections
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Jun 11, 2025 - Python
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.
kernel-methods rkhs gaussian-processes bayesian-optimization active-learning approximate-inference kernel-embeddings kernel-mean-embeddings conditional-mean-embeddings
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Aug 19, 2022 - Python
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Apr 8, 2018 - Python
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