variational-inference

There are 11 repositories under variational-inference topic.

svc-develop-team / so-vits-svc
SoftVC VITS Singing Voice Conversion
ai audio-analysis deep-learning flow generative-adversarial-network pytorch singing-voice-conversion so-vits-svc sovits speech variational-inference vc vits voice voice-changer voice-conversion voiceconversion
Language:Python 27746
pymc-devs / pymc
Bayesian Modeling and Probabilistic Programming in Python
bayesian-inference mcmc probabilistic-programming pytensor python statistical-analysis variational-inference
Language:Python 9344
pyro
pyro-ppl / pyro
Deep universal probabilistic programming with Python and PyTorch
bayesian bayesian-inference deep-learning machine-learning probabilistic-modeling probabilistic-programming python pytorch variational-inference
Language:Python 8901
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 1934
GPflow / GPflow
Gaussian processes in TensorFlow
gaussian-processes tensorflow gpflow machine-learning variational-inference bayesian-statistics markov-chain-monte-carlo stochastic-processes deep-learning ml gp
Language:Python 1889
janosh / awesome-normalizing-flows
Awesome resources on normalizing flows.
autoregressive awesome-list bayesian-inference bayesian-neural-networks density-estimation generative-modeling machine-learning normalizing-flows variational-inference
Language:Python 1578
kumar-shridhar / PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
convolutional-neural-networks bayesian-network bayesian-convnets bayes-by-backprop pytorch python pytorch-cnn bayesian-neural-networks bayesian-deep-learning bayesian-inference bayesian-statistics image-recognition aleatoric-uncertainties bayes bayesian-networks variational-inference variational-bayes
Language:Python 1536
jaanli / variational-autoencoder
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
vae machine-learning tensorflow variational-autoencoder variational-inference probabilistic-graphical-models deep learning deep-learning deep-neural-networks pytorch unsupervised-learning autoregressive-neural-networks
Language:Python 1174
bayesgroup / deepbayes-2018
Seminars DeepBayes Summer School 2018
deep-learning bayesian variational-inference
Language:Jupyter Notebook 1046
neka-nat / probreg
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
3d coherent-point-drift dual-quaternion dual-quaternion-skinning expectation-maximization-algorithm filterreg gaussian-mixture-models non-rigid-registration open3d point-cloud point-cloud-registration registration rigid-transformations variational-inference
Language:Python 936
VincentStimper / normalizing-flows
PyTorch implementation of normalizing flow models
normalizing-flow variational-autoencoder variational-inference real-nvp residual-flow glow pytorch neural-spline-flow density-estimation invertible-neural-networks
Language:Python 900
yell / boltzmann-machines
Boltzmann Machines in TensorFlow with examples
ais annealed-importance-sampling boltzmann-machines contrastive-divergence-algorithm dbm deep-learning energy-based-model gibbs-sampling keras machine-learning mcmc pcd rbm restricted-boltzmann-machine sklearn-compatible tensorflow tensorflow-models variational-inference
Language:Jupyter Notebook 850
matthewvowels1 / Awesome-VAEs
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
awesome-list deep-learning disentangled-representations disentanglement generative-model representation-learning unsupervised-learning vae variational-auto-encoder variational-autoencoder variational-bayes variational-inference
830
bahjat-kawar / ddrm
[NeurIPS 2022] Denoising Diffusion Restoration Models -- Official Code Repository
diffusion deblurring diffusion-models inpainting inverse-problems score-based super-resolution variational-inference
Language:Python 652
SimonKohl / probabilistic_unet
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
generative-models neurips neurips-2018 nips nips-2018 semantic-segmentation u-net variational-autoencoders variational-inference
Language:Jupyter Notebook 561
sjchoi86 / bayes-nn
Lecture notes on Bayesian deep learning
deep-learning probability-theory variational-inference
488
fehiepsi / rethinking-numpyro
Statistical Rethinking (2nd ed.) with NumPyro
bayesian-statistics laplace-approximation markov-chain-monte-carlo causal-inference variational-inference python numpy
Language:Jupyter Notebook 463
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
393
ReactiveBayes / RxInfer.jl
Julia package for automated Bayesian inference on a factor graph with reactive message passing
bayesian-inference inference-engine julia-language machine-learning message-passing probabilistic-programming variational-inference
Language:Jupyter Notebook 371
omerbsezer / Generative_Models_Tutorial_with_Demo
Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..
variational-autoencoder generative-adversarial-network gans dcgan cyclegan generative-model tutorial tutorial-code variational-inference gaussian-mixture-models auto-regressive-model bayesian-classifiers
Language:Jupyter Notebook 339
ohirose / bcpd
Bayesian Coherent Point Drift / Domain Elastic Transform
shape-analysis non-rigid-registration variational-inference shape-deformation point-cloud-registration shape-matching point-set-registration downsampling gaussian-processes bayesian-inference outlier-detection coherent-point-drift
Language:C 331
hoangcuong2011 / Good-Papers
I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers
deep-learning machine-learning natural-language-processing computer-vision gaussian-processes variational-autoencoders neural-machine-translation neural-network convolutional-networks semi-supervised-learning variational-inference kernel-learning representation-learning deep-kernel-learning
285
ksachdeva / rethinking-tensorflow-probability
Statistical Rethinking (2nd Ed) with Tensorflow Probability
tensorflow tensorflow-probability bayesian-inference bayesian-statistics statistical-rethinking tutorials markov-chain-monte-carlo variational-inference
Language:Jupyter Notebook 272
wiseodd / probabilistic-models
Collection of probabilistic models and inference algorithms
probabilistic-models python machine-learning bayesian bayesian-inference mcmc gibbs-sampling variational-inference dirichlet-process
Language:Python 241
ex4sperans / variational-inference-with-normalizing-flows
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
machine-learning variational-inference density-estimation python pytorch normalizing-flows
Language:Python 237
acerbilab / vbmc
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
bayesian-inference data-analysis gaussian-processes machine-learning matlab variational-inference
Language:MATLAB 229
ermongroup / Variational-Ladder-Autoencoder
Implementation of VLAE
generative-model variational-inference unsupervised-learning feature-extraction representation-learning
Language:Python 216
1Konny / VIB-pytorch
Pytorch implementation of Deep Variational Information Bottleneck
deep-learning machine-learning information-bottleneck variational-inference classification pytorch
Language:Python 201
jeff-regier / Celeste.jl
Scalable inference for a generative model of astronomical images
astronomy bayesian-inference variational-inference astronomical-catalogs astronomical-images graphical-models
Language:Jupyter Notebook 187
nitarshan / bayes-by-backprop
PyTorch implementation of "Weight Uncertainty in Neural Networks"
pytorch bayes-by-backprop bayesian-deep-learning bayesian-neural-networks variational-inference
Language:Jupyter Notebook 176
gpstuff-dev / gpstuff
GPstuff - Gaussian process models for Bayesian analysis
bayesian bayesian-inference bayesian-optimization classification covariance-functions expectation-propagation gaussian-processes mcmc octave regression spatial-analysis survival-analysis variational-inference
Language:MATLAB 175
stan-dev / cmdstanr
CmdStanR: the R interface to CmdStan
r-package stan bayesian mcmc variational-inference maximum-likelihood markov-chain-monte-carlo bayes
Language:R 154
hwalsuklee / tensorflow-mnist-CVAE
Tensorflow implementation of conditional variational auto-encoder for MNIST
tensorflow mnist vae cvae denoising denoising-autoencoders denoising-images variational-autoencoder variational-inference autoencoder conditional conditional-vae
Language:Python 150
simonkamronn / kvae
Kalman Variational Auto-Encoder
deep-learning kalman-filter neural-network graphical-models variational-inference variational-autoencoder
Language:Python 136
abdulfatir / normalizing-flows
Understanding normalizing flows
variational-inference normalizing-flows deep-learning variational-autoencoder
Language:Jupyter Notebook 132
acerbilab / pyvbmc
PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python
bayesian-inference data-analysis gaussian-processes machine-learning python variational-inference
Language:Python 121

variational-inference

svc-develop-team / so-vits-svc

pymc-devs / pymc

pyro-ppl / pyro

JavierAntoran / Bayesian-Neural-Networks

GPflow / GPflow

janosh / awesome-normalizing-flows

kumar-shridhar / PyTorch-BayesianCNN

jaanli / variational-autoencoder

bayesgroup / deepbayes-2018

neka-nat / probreg

VincentStimper / normalizing-flows

yell / boltzmann-machines

matthewvowels1 / Awesome-VAEs

bahjat-kawar / ddrm

SimonKohl / probabilistic_unet

sjchoi86 / bayes-nn

fehiepsi / rethinking-numpyro

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

ReactiveBayes / RxInfer.jl

omerbsezer / Generative_Models_Tutorial_with_Demo

ohirose / bcpd

hoangcuong2011 / Good-Papers

ksachdeva / rethinking-tensorflow-probability

wiseodd / probabilistic-models

ex4sperans / variational-inference-with-normalizing-flows

acerbilab / vbmc

ermongroup / Variational-Ladder-Autoencoder

1Konny / VIB-pytorch

jeff-regier / Celeste.jl

nitarshan / bayes-by-backprop

gpstuff-dev / gpstuff

stan-dev / cmdstanr

hwalsuklee / tensorflow-mnist-CVAE

simonkamronn / kvae

abdulfatir / normalizing-flows

acerbilab / pyvbmc