approximate-inference

There are 1 repository under approximate-inference topic.

JavierAntoran / Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
deep-learning bayesian-inference pytorch reproducible-research bayesian-neural-networks bayes-by-backprop mc-dropout mcmc variational-inference kronecker-factored-approximation langevin-dynamics approximate-inference local-reparametrization-trick uncertainty uncertainty-neural-networks out-of-distribution-detection classification regression sgld hmc
Language:Jupyter Notebook 1749
FranxYao / Deep-Generative-Models-for-Natural-Language-Processing
DGMs for NLP. A roadmap.
generative-model generative-text text-generation generative-models latent-variable-models variational-inference variational-autoencoders generative-adversarial-networks normalizing-flows parsing approximate-inference graphical-models natural-language-processing mcmc markov-chain-monte-carlo structured-prediction gradient-estimation discrete-structures language-model decoding
389
JuliaGaussianProcesses / Stheno.jl
Probabilistic Programming with Gaussian processes in Julia
approximate-inference bayesian-inference gaussian-processes machine-learning probabilistic-programming
Language:Julia 333
joennlae / halutmatmul
Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator
machine-learning pytorch approximate-inference hardware hardware-acceleration maddness
Language:Python 202
Phylliade / awesome-machine-learning-robotics
A curated list of resources about Machine Learning for Robotics
approximate-inference awesome awesome-list curriculum-learning deep-learning deep-reinforcement-learning machine-learning reinforcement-learning robotics
143
akosiorek / sqair
Implementation of Sequential Attend, Infer, Repeat (SQAIR)
sqair vae generative representations-learning detection tracking motion approximate-inference variational-inference vimco iwae
Language:Jupyter Notebook 96
dflemin3 / approxposterior
A Python package for approximate Bayesian inference and optimization using Gaussian processes
approximate-inference bayesian-inference bayesian-optimization gaussian-processes inference python
Language:Python 40
YingzhenLi / Dropout_BBalpha
Implementations of the ICML 2017 paper (with Yarin Gal)
deep-learning bayesian bayesian-deep-learning approximate-inference
Language:Python 39
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"
approximate-inference bayes-by-backprop bayesian-inference bayesian-neural-networks deep-learning hmc kronecker-factored-approximation langevin-dynamics local-reparametrization-trick mcmc sgld uncertainty uncertainty-neural-networks variational-inference
35
JoeMWatson / input-inference-for-control
Input Inference for Control (i2c), a control-as-inference framework for optimal control
inference trajectory-optimization approximate-inference control robotics control-as-inference
Language:Python 21
ermongroup / SPN_Variational_Inference
PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
pytorch variational-inference sum-product-networks probabilistic-circuits graphical-models approximate-inference
Language:Python 15
compops / gpo-smc-abc
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
gaussian-process-optimisation bayesian-optimization approximate-inference approximate-bayesian-computation stochastic-volatility-models alpha-stable-processes portfolio-analysis gaussian-processes particle-filter
Language:Python 12
ocramz / bayesian-inference
bayesian-inference bayesian-statistics inference statistical-learning machine-learning approximate-bayesian-computation approximate-inference statistical-inference machine-learning-library
Language:Haskell 7
Sheev13 / bnn-mean-field-vi
approximate-inference bayesian-deep-learning bayesian-inference bayesian-neural-networks deep-learning machine-learning variational-inference mean-field-approximation mean-field-variational-inference pytorch
Language:Jupyter Notebook 6
tkusmierczyk / lcvi
Variational Bayesian decision-making for continuous utilities
decision-making bayesian-inference variational-inference approximate-inference pytorch-implementation machine-learning
Language:Jupyter Notebook 6
lacerbi / infbench
Benchmark of posterior and model inference algorithms for (moderately) expensive likelihoods.
benchmark approximate-inference modeling model-selection computational-neuroscience
Language:MATLAB 5
ztanml / arLMM
Approximate Ridge Linear Mixed Models (arLMM)
linear-mixed-models linear-mixed-effects-modelling hierarchical-models randomized-algorithm approximate-inference approximate-algorithms low-rank-approximation
Language:C 4
parthnatekar / Loopy-Belief-Propagation
An implementation of loopy belief propagation for binary image denoising. Both sequential and parallel updates are implemented.
loopy-belief-propagation approximate-inference belief-propagation ising-model probabilistic-graphical-models loopy-bp
Language:Python 3
Sheev13 / bayesian-inference
approximate-inference bayesian-inference bayesian-logistic-regression classification laplace-approximation logistic-regression machine-learning probabilistic-machine-learning inference 3f8
Language:Jupyter Notebook 2
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.
dee-learning deep-neural-networks bayesian-deep-learning approximate-inference
Language:Python 2
Af4rinz / stot
STOT: Single-Target Object Tracking using particle and Kalman filters [with a bonus multi-target].
object-tracking particle-filter pgm approximate-inference kalman-filter
Language:Jupyter Notebook 1
dirmeier / ssnl
Simulation-based inference using SSNL
approximate-bayesian-computation approximate-inference bayesian-inference jax normalizing-flows simulation-based-inference
Language:Python 1
lpcinelli / probabilistic-nn
Probabilistic approach to neural nets - modern scalable approximate inference methods
bayesian-neural-networks variational-inference approximate-inference monte-carlo-dropout expectation-propagation
Language:Jupyter Notebook 1
sanjeevg15 / loopy-bp-denoise
Denoise a given image using Loopy Belief Propagation
loopy-belief-propagation probabilistic-graphical-models approximate-inference loopy-bp bethe-cluster-graph denoise noise-removal
Language:Jupyter Notebook 1
tkusmierczyk / correcting_approximate_bayesian_predictions
Correcting predictions for approximate Bayesian inference
machine-learning bayesian-inference decision-making approximate-inference
Language:Jupyter Notebook 1
chrise592 / probabilistic_propositions
python artificial-intelligence bayesian-networks approximate-inference
Language:Python 0
ErfanXH / Sampling
Implementation of Prior, Rejection, Likelihood and Gibbs Sampling
approximate-inference exact-inference gibbs-sampling inference likelihood prior-sampling rejection-sampling sampling sampling-methods
Language:Python 0
jswu18 / approximate-inference
Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression
approximate-inference automatic-relevance-determination expectation-maximisation gaussian-process-regression loopy-belief-propagation mean-field-approximation variational-bayes
Language:Python 0
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.
active-learning approximate-inference bayesian-optimization conditional-mean-embeddings gaussian-processes kernel-embeddings kernel-mean-embeddings kernel-methods rkhs
Language:Python 0
rafaol / no-regret-approximate-inference-via-bo
Code repository for the paper No-Regret Approximate Inference via Bayesian Optimisation, published at UAI 2021
approximate-inference bandit-algorithms bayesian-inference bayesian-optimization gaussian-processes mcmc pytorch-implementation
Language:Jupyter Notebook 0
riccmon / Employee-Attrition
FAIKR MOD3 project
approximate-inference bayesian-networks exact-inference inferences pgmpy reasoning-patterns artificial-intelligence
Language:Jupyter Notebook 0
zimmerman-cole / hons-proj-public
My undergraduate honours project, with others' private information/code removed.
bayesian-optimization gaussian-process-regression approximate-inference parameter-estimation
Language:OpenEdge ABL 0
AaltoML / improved-hyperparameter-learning
Codes for 'Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models' (ICML 2023)
approximate-inference expectation-propagation gaussian-processes variational-inference
Language:Jupyter Notebook

approximate-inference

JavierAntoran / Bayesian-Neural-Networks

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

JuliaGaussianProcesses / Stheno.jl

joennlae / halutmatmul

Phylliade / awesome-machine-learning-robotics

akosiorek / sqair

dflemin3 / approxposterior

YingzhenLi / Dropout_BBalpha

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

JoeMWatson / input-inference-for-control

ermongroup / SPN_Variational_Inference

compops / gpo-smc-abc

ocramz / bayesian-inference

Sheev13 / bnn-mean-field-vi

tkusmierczyk / lcvi

lacerbi / infbench

ztanml / arLMM

parthnatekar / Loopy-Belief-Propagation

Sheev13 / bayesian-inference

tmgrgg / localvsglobaluncertainty

Af4rinz / stot

dirmeier / ssnl

lpcinelli / probabilistic-nn

sanjeevg15 / loopy-bp-denoise

tkusmierczyk / correcting_approximate_bayesian_predictions

chrise592 / probabilistic_propositions

ErfanXH / Sampling

jswu18 / approximate-inference

rafaol / active-learning-conditional-mean-embeddings

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

riccmon / Employee-Attrition

zimmerman-cole / hons-proj-public

AaltoML / improved-hyperparameter-learning