variational-inference

There are 424 repositories under variational-inference topic.

  • VGRNN

    Variational Graph Recurrent Neural Networks - PyTorch

    Language:Python114

  • ReactiveMP.jl

    High-performance reactive message-passing based Bayesian inference engine

    Language:Julia109

  • MXFusion

    Modular Probabilistic Programming on MXNet

    Language:Python104

  • sqair

    Implementation of Sequential Attend, Infer, Repeat (SQAIR)

    Language:Jupyter Notebook97

  • inverse_rl

    Adversarial Imitation Via Variational Inverse Reinforcement Learning

    Language:Python95

  • ladder-vae-pytorch

    Ladder Variational Autoencoders (LVAE) in PyTorch

    Language:Python89

  • Dropouts

    PyTorch Implementations of Dropout Variants

    Language:Jupyter Notebook87

  • posterior-collapse-list

    A curated list of techniques to avoid posterior collapse

    85

  • deep-active-inference-mc

    Deep active inference agents using Monte-Carlo methods

    Language:Python84

  • Sequential-Variational-Autoencoder

    Implementation of Sequential Variational Autoencoder

    Language:Python84

  • gelato

    Bayesian dessert for Lasagne

    Language:Python84

  • BayeSeg

    [MedIA Best Paper Award] Official implementation of MedIA paper "BayeSeg: Bayesian Modelling for Medical Image Segmentation with Interpretable Generalizability"

    Language:Python81

  • variational-diffusion-models

    PyTorch implementation of Variational Diffusion Models.

    Language:Python77

  • Pathfinder.jl

    Preheat your MCMC

    Language:Julia77

  • vireo

    Demultiplexing pooled scRNA-seq data with or without genotype reference

    Language:Python73

  • DUN

    Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

    Language:Jupyter Notebook72

  • variational-item-response-theory-public

    A PyTorch implementation of "Variational Item Response Theory: Fast Accurate, and Expressive"

    Language:Python72

  • tf-var-attention

    Tensorflow Implementation of Variational Attention for Sequence to Sequence Models (COLING 2018)

    Language:Python69

  • MOVE

    MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

    Language:Jupyter Notebook66

  • Generalized-PixelVAE

    PixelVAE with or without regularization

    Language:Python66

  • BayesByHypernet

    Code for the paper Implicit Weight Uncertainty in Neural Networks

    Language:Jupyter Notebook65

  • Bayesian-Methods-for-Machine-Learning

    Bayesian Methods for Machine Learning

    Language:Jupyter Notebook64

  • wae-rnf-lm

    Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

    Language:Python62

  • NoisyNaturalGradient

    TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".

    Language:Python60

  • mvae

    Mixed-curvature Variational Autoencoders (ICLR 2020)

    Language:Python58

  • AI_Learning_Hub

    AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

    Language:HTML58

  • MCDO

    A pytorch implementation of MCDO(Monte-Carlo Dropout methods)

    Language:Jupyter Notebook56

  • avici

    Amortized Inference for Causal Structure Learning, NeurIPS 2022

    Language:Python55

  • ivon

    IVON optimizer for neural networks based on variational learning.

    Language:Python54

  • AVUC

    Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

    Language:Python53

  • topic-rnn

    Implementation (in progress) of Dieng et al.'s TopicRNN: a neural topic model & RNN hybrid.

    Language:Python53

  • SIVI

    A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural networks and hierarchical distribution (ICML 2018).

    Language:MATLAB53

  • generative-modeling-explained

    Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.

    50

  • PyLDA

    A Latent Dirichlet Allocation implementation in Python.

    Language:Python50

  • 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"

    49

  • probai-2021-pyro

    Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)

    Language:Jupyter Notebook47