Ecosyste.ms: Awesome

https://github.com/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

Last synced: 29 Sep 2024

https://github.com/pymc-devs/pymc

Bayesian Modeling and Probabilistic Programming in Python

bayesian-inference mcmc probabilistic-programming pytensor python statistical-analysis variational-inference

Last synced: 13 Jan 2025

https://github.com/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

Last synced: 13 Jan 2025

https://github.com/javierantoran/bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

approximate-inference bayes-by-backprop bayesian-inference bayesian-neural-networks classification deep-learning hmc kronecker-factored-approximation langevin-dynamics local-reparametrization-trick mc-dropout mcmc out-of-distribution-detection pytorch regression reproducible-research sgld uncertainty uncertainty-neural-networks variational-inference

Last synced: 18 Jan 2025

https://github.com/GPflow/GPflow

Gaussian processes in TensorFlow

bayesian-statistics deep-learning gaussian-processes gp gpflow machine-learning markov-chain-monte-carlo ml stochastic-processes tensorflow variational-inference

Last synced: 05 Nov 2024

https://github.com/gpflow/gpflow

Gaussian processes in TensorFlow

bayesian-statistics deep-learning gaussian-processes gp gpflow machine-learning markov-chain-monte-carlo ml stochastic-processes tensorflow variational-inference

Last synced: 14 Jan 2025

https://github.com/JavierAntoran/Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

approximate-inference bayes-by-backprop bayesian-inference bayesian-neural-networks classification deep-learning hmc kronecker-factored-approximation langevin-dynamics local-reparametrization-trick mc-dropout mcmc out-of-distribution-detection pytorch regression reproducible-research sgld uncertainty uncertainty-neural-networks variational-inference

Last synced: 12 Nov 2024

https://github.com/kumar-shridhar/pytorch-bayesiancnn

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

aleatoric-uncertainties bayes bayes-by-backprop bayesian-convnets bayesian-deep-learning bayesian-inference bayesian-network bayesian-networks bayesian-neural-networks bayesian-statistics convolutional-neural-networks image-recognition python pytorch pytorch-cnn variational-bayes variational-inference

Last synced: 18 Jan 2025

https://github.com/kumar-shridhar/PyTorch-BayesianCNN

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

aleatoric-uncertainties bayes bayes-by-backprop bayesian-convnets bayesian-deep-learning bayesian-inference bayesian-network bayesian-networks bayesian-neural-networks bayesian-statistics convolutional-neural-networks image-recognition python pytorch pytorch-cnn variational-bayes variational-inference

Last synced: 30 Oct 2024

https://github.com/jaanli/variational-autoencoder

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

autoregressive-neural-networks deep deep-learning deep-neural-networks learning machine-learning probabilistic-graphical-models pytorch tensorflow unsupervised-learning vae variational-autoencoder variational-inference

Last synced: 18 Jan 2025

https://github.com/bayesgroup/deepbayes-2018

Seminars DeepBayes Summer School 2018

bayesian deep-learning variational-inference

Last synced: 20 Jan 2025

https://github.com/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

Last synced: 17 Jan 2025

https://github.com/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

Last synced: 15 Jan 2025

https://github.com/VincentStimper/normalizing-flows

PyTorch implementation of normalizing flow models

density-estimation glow invertible-neural-networks neural-spline-flow normalizing-flow pytorch real-nvp residual-flow variational-autoencoder variational-inference

Last synced: 17 Nov 2024

https://github.com/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

Last synced: 27 Nov 2024

https://github.com/sjchoi86/bayes-nn

Lecture notes on Bayesian deep learning

deep-learning probability-theory variational-inference

Last synced: 25 Nov 2024

https://github.com/fehiepsi/rethinking-numpyro

Statistical Rethinking (2nd ed.) with NumPyro

bayesian-statistics causal-inference laplace-approximation markov-chain-monte-carlo numpy python variational-inference

Last synced: 18 Jan 2025

https://github.com/franxyao/deep-generative-models-for-natural-language-processing

DGMs for NLP. A roadmap.

approximate-inference decoding discrete-structures generative-adversarial-networks generative-model generative-models generative-text gradient-estimation graphical-models language-model latent-variable-models markov-chain-monte-carlo mcmc natural-language-processing normalizing-flows parsing structured-prediction text-generation variational-autoencoders variational-inference

Last synced: 11 Jan 2025

https://github.com/franxyao/Deep-Generative-Models-for-Natural-Language-Processing

DGMs for NLP. A roadmap.

approximate-inference decoding discrete-structures generative-adversarial-networks generative-model generative-models generative-text gradient-estimation graphical-models language-model latent-variable-models markov-chain-monte-carlo mcmc natural-language-processing normalizing-flows parsing structured-prediction text-generation variational-autoencoders variational-inference

Last synced: 10 Nov 2024

https://github.com/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..

auto-regressive-model bayesian-classifiers cyclegan dcgan gans gaussian-mixture-models generative-adversarial-network generative-model tutorial tutorial-code variational-autoencoder variational-inference

Last synced: 16 Jan 2025

https://github.com/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..

auto-regressive-model bayesian-classifiers cyclegan dcgan gans gaussian-mixture-models generative-adversarial-network generative-model tutorial tutorial-code variational-autoencoder variational-inference

Last synced: 27 Nov 2024

https://github.com/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

computer-vision convolutional-networks deep-kernel-learning deep-learning gaussian-processes kernel-learning machine-learning natural-language-processing neural-machine-translation neural-network representation-learning semi-supervised-learning variational-autoencoders variational-inference

Last synced: 27 Nov 2024

https://github.com/ksachdeva/rethinking-tensorflow-probability

Statistical Rethinking (2nd Ed) with Tensorflow Probability

bayesian-inference bayesian-statistics markov-chain-monte-carlo statistical-rethinking tensorflow tensorflow-probability tutorials variational-inference

Last synced: 16 Jan 2025

https://github.com/wiseodd/probabilistic-models

Collection of probabilistic models and inference algorithms

bayesian bayesian-inference dirichlet-process gibbs-sampling machine-learning mcmc probabilistic-models python variational-inference

Last synced: 16 Jan 2025

https://github.com/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

Last synced: 16 Jan 2025

https://github.com/ermongroup/variational-ladder-autoencoder

Implementation of VLAE

feature-extraction generative-model representation-learning unsupervised-learning variational-inference

Last synced: 18 Nov 2024

https://github.com/jeff-regier/Celeste.jl

Scalable inference for a generative model of astronomical images

astronomical-catalogs astronomical-images astronomy bayesian-inference graphical-models variational-inference

Last synced: 12 Nov 2024

https://github.com/hwalsuklee/tensorflow-mnist-cvae

Tensorflow implementation of conditional variational auto-encoder for MNIST

autoencoder conditional conditional-vae cvae denoising denoising-autoencoders denoising-images mnist tensorflow vae variational-autoencoder variational-inference

Last synced: 14 Oct 2024

https://github.com/stan-dev/cmdstanr

CmdStanR: the R interface to CmdStan

bayes bayesian markov-chain-monte-carlo maximum-likelihood mcmc r-package stan variational-inference

Last synced: 15 Jan 2025

https://github.com/abdulfatir/normalizing-flows

Understanding normalizing flows

deep-learning normalizing-flows variational-autoencoder variational-inference

Last synced: 05 Dec 2024

https://github.com/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

Last synced: 18 Jan 2025

https://github.com/amzn/MXFusion

Modular Probabilistic Programming on MXNet

bayesian-inference machine-learning mxnet probabilistic-programming python variational-inference

Last synced: 08 Nov 2024

https://github.com/akosiorek/sqair

Implementation of Sequential Attend, Infer, Repeat (SQAIR)

approximate-inference detection generative iwae motion representations-learning sqair tracking vae variational-inference vimco

Last synced: 10 Oct 2024

https://github.com/biaslab/ReactiveMP.jl

High-performance reactive message-passing based Bayesian inference engine

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: 14 Nov 2024

https://github.com/reactivebayes/reactivemp.jl

High-performance reactive message-passing based Bayesian inference engine

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: 21 Nov 2024

https://github.com/ReactiveBayes/ReactiveMP.jl

High-performance reactive message-passing based Bayesian inference engine

bayesian-inference inference julia message-passing probabilistic-graphical-models probabilistic-programming variational-bayes variational-inference

Last synced: 13 Nov 2024

https://github.com/j-min/dropouts

PyTorch Implementations of Dropout Variants

bayesian-neural-networks dropout gaussian-dropout local-reparametrization-trick pytorch variational-dropout variational-inference

Last synced: 19 Nov 2024

https://github.com/ferrine/gelato

Bayesian dessert for Lasagne

bayesian-inference deep-learning gelato lasagne neural-network theano uncertainty variational-inference

Last synced: 28 Oct 2024

https://github.com/ermongroup/sequential-variational-autoencoder

Implementation of Sequential Variational Autoencoder

generative-model variational-inference

Last synced: 18 Nov 2024

https://github.com/mhw32/variational-item-response-theory-public

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

bayesian-inference education item-response-theory variational-inference

Last synced: 10 Dec 2024

https://github.com/pomonam/noisynaturalgradient

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

bayesian-inference bayesian-neural-networks natural-gradients variational-inference

Last synced: 06 Jan 2025

https://github.com/SHI-Yu-Zhe/generative-modeling-explained

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

adversarial-learning bayesian-inference diffusion-model energy-based-model equilibrium-sampling generative-modeling langevin-dynamics mcmc-sampling non-equilibrium-sampling score-based-generative-modeling variational-inference

Last synced: 19 Nov 2024

https://github.com/kourouklides/artificial_neural_networks

A collection of Methods and Models for various architectures of Artificial Neural Networks

artificial-neural-networks bayesian-inference bayesian-learning bayesian-neural-networks data-science deep-learning deep-neural-networks edward edward2 keras machine-learning machine-learning-algorithms machinelearning neural-networks probabilistic-modeling probabilistic-models python tensorflow variational-inference

Last synced: 18 Nov 2024

https://github.com/thjashin/gp-infer-net

Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019

gaussian-processes variational-inference

Last synced: 13 Nov 2024

https://github.com/snowkylin/rnn-vae

Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"

autoencoder draw image-generation recurrent-neural-networks variational-inference

Last synced: 15 Nov 2024

https://github.com/tomekkorbak/active-inference

A toy model of Friston's active inference in Tensorflow

cognitive-science deep-learning free-energy tensorflow variational-inference

Last synced: 22 Oct 2024

https://github.com/sunsided/vae-style-transfer

An experiment in VAE-based artistic style transfer by embedding fiddling.

artificial-intelligence autoencoder cadl deep-learning experiment generative-adversarial-network generative-art image-processing kadenze neural-network online-course tensorflow vae vaegan variational-inference

Last synced: 10 Oct 2024

https://github.com/vLAR-group/UnsupObjSeg

🔥Benchmarking Unsupervised Obj Seg (NeurIPS 2022 & IJCV 2024)

benchmarking generative-model instance-segmentation neurips-2022 object-centric object-detection object-segmentation real-world-images unsupervised-learning variational-autoencoder variational-inference

Last synced: 28 Oct 2024

https://github.com/gd-zhang/noisy-k-fac

Natural Gradient, Variational Inference

bayesian-inference bayesian-neural-networks natural-gradients uncertainty-estimation variational-inference

Last synced: 13 Jan 2025

https://github.com/ermongroup/lagvae

Lagrangian VAE

generative-adversarial-network tensorflow variational-autoencoder variational-inference

Last synced: 18 Nov 2024

https://github.com/robert-giaquinto/gradient-boosted-normalizing-flows

We got a stew going!

boosting deep-generative-model density-estimation normalizing-flows pytorch variational-autoencoder variational-inference

Last synced: 10 Nov 2024

https://github.com/pierresegonne/VINF

Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen

distributions python3 tensorflow variational-inference

Last synced: 17 Nov 2024

https://github.com/pierresegonne/vinf

Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen

distributions python3 tensorflow variational-inference

Last synced: 15 Oct 2024

https://github.com/4ment/phylostan

Phylogenetic inference using Stan

bayes hmc phylogenetics pystan stan variational-inference

Last synced: 07 Nov 2024

https://github.com/yjlolo/pytorch-deep-markov-model

PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]

aaai markov-model pytorch-implementation reimplementation sequential-data variational-autoencoders variational-inference

Last synced: 15 Oct 2024

https://github.com/cbg-ethz/scdef

Deep exponential families for single-cell data.

batch-integration gene-signatures hierarchical-models jax matrix-factorization scrna-seq single-cell-rna-seq variational-inference

Last synced: 17 Nov 2024

https://github.com/citiususc/voila

Variational Inference for Langevin Equations

diffusion drift ecology gaussian-processes langevin-equations r r-package stochastic-differential-equations variational-inference

Last synced: 02 Dec 2024

https://github.com/lucastheis/trlda

Implementations of various online inference algorithms for LDA, with Python interface.

lda machine-learning python topic-modeling variational-inference

Last synced: 13 Nov 2024

https://github.com/karenullrich/binary-vae

A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.

bernoulli binary concrete-distribution tensorflow tensorflow-eager tensorflow-probability vae variational-autoencoder variational-inference

Last synced: 27 Oct 2024

https://github.com/lucadellalib/bdl-rul-svgd

Bayesian deep learning for remaining useful life estimation via Stein variational gradient descent

bayes-by-backprop bayesian-deep-learning bayesian-inference bayesian-neural-networks c-mapss deep-learning machine-learning predictive-maintenance python pytorch remaining-useful-life stein-variational-gradient-descent variational-inference

Last synced: 29 Dec 2024

https://github.com/maximevandegar/normalizing-flows

A repository to learn about Flows, mostly from papers

density-estimation generative-model inference normalizing-flows variational-inference

Last synced: 28 Nov 2024

https://github.com/const-ae/mixdir

Cluster high dimensional categorical datasets

categorical-data clustering questionnaires r-package variational-inference

Last synced: 14 Jan 2025

https://github.com/ermongroup/spn_variational_inference

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

approximate-inference graphical-models probabilistic-circuits pytorch sum-product-networks variational-inference

Last synced: 18 Nov 2024

https://github.com/andreaskapou/Melissa

Bayesian Clustering and Imputation of Single Cell Methylomes

bayesian-inference clustering imputation methylation variational-inference

Last synced: 06 Nov 2024

https://github.com/4ment/physher

A multi-algorithmic framework for phylogenetic inference

bayesian-inference c genetic-algorithm maximum-likelihood mcmc phylogenetics variational-inference

Last synced: 07 Nov 2024

https://github.com/rguo12/CIKM18-LCVA

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

causal-inference network-embedding treatment-effects variational-autoencoder variational-inference

Last synced: 03 Nov 2024

https://github.com/4ment/torchtree

A probabilistic framework in PyTorch for phylogenetic models

phylogenetics pytorch variational-inference

Last synced: 07 Nov 2024

https://github.com/alexioannides/pymc-advi-hmc-demo

Demonstrating HMC and ADVI algorithms for Bayesian data analysis using PYMC3.

bayesian-data-analysis bayesian-inference data-science example-project jupyter-notebook machine-learning markov-chain-monte-carlo probabilistic-programming pymc3 python variational-inference

Last synced: 12 Oct 2024

https://github.com/Himscipy/bnn_hvd

Distributed Training of Bayesian Neural Networks at Scale

bayesian-networks computer-vision data-science distributed-computing horovod machine-learning mnist tensorflow tensorflow-probability uncertainty-quantification variational-inference

Last synced: 23 Nov 2024

https://github.com/senya-ashukha/sparse-vd-pytorch

Sparse Variational Dropout a a Minimal Working Example

deep-learning sparse-dnn variational-dropout variational-inference

Last synced: 19 Nov 2024

https://github.com/lucadellalib/bayestorch

Lightweight Bayesian deep learning library for fast prototyping based on PyTorch

bayes-by-backprop bayesian-deep-learning bayesian-inference bayesian-neural-networks deep-learning machine-learning markov-chain-monte-carlo python pytorch stein-variational-gradient-descent uncertainty-quantification variational-inference

Last synced: 07 Nov 2024

https://github.com/mancusolab/FactorGo

Software to infer latent pleiotropic components from GWAS summary data

gwas gwas-summary-statistics jax variational-inference

Last synced: 03 Dec 2024

https://github.com/dongjunlee/vae-tensorflow

TensorFlow implementation of Auto-Encoding Variational Bayes.

generative-model hb-experiment mnist tensorflow variational-autoencoders variational-inference

Last synced: 01 Jan 2025

https://github.com/zafarali/generative

Repository to explore Generative Models

generative-model machine-learning variational-inference

Last synced: 13 Oct 2024

https://github.com/ermongroup/streamline-vi-csp

belief-propagation constraint-satisfaction-problem nips-2018 sat-solver satisfiability variational-inference

Last synced: 18 Nov 2024

https://github.com/yeonghyeon/normalizing-flow-tf2

TensorFlow implementation of "Variational Inference with Normalizing Flows"

distribution mnist mnist-dataset normalizing-flow tensorflow tensorflow2 variational-inference

Last synced: 11 Nov 2024

https://github.com/mhw32/antithetic-vae-public

PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).

aistats sampling-methods variance-reduction variational-autoencoder variational-inference

Last synced: 10 Dec 2024

https://github.com/robbenribery/tuotuo

TuoTuo is a Topic Modeling library for Researchers and Engineers

attention attention-mechanism bayesian-inference gpt language-model latent-dirichlet-allocation natural-language-processing pytorch topic-modeling transformer unsupervised-learning variational-inference

Last synced: 10 Nov 2024

https://github.com/andreofner/pygpc

Generalized Predictive Coding in Torch

deep-learning free-energy-principle generative-model predictive-coding predictive-processing variational-inference

Last synced: 07 Jan 2025

https://github.com/silvanmelchior/cbf-ssm

Official implementation of the CBF-SSM model

gaussian-processes machine-learning state-space-models variational-inference

Last synced: 06 Dec 2024

https://github.com/piyush-555/vcl-in-pytorch

PyTorch implementation of Variational Continual Learning

bayesian-neural-networks continual-learning lifelong-learning pytorch variational-inference

Last synced: 14 Oct 2024

https://github.com/clberube/ip-vae

PyTorch implementation of the time-domain induced polarization variational autoencoder

deep-learning geophysics induced-polarization neural-network pytorch variational-autoencoder variational-inference

Last synced: 19 Nov 2024

https://github.com/mohamedhmini/paysim-fraud-detection-using-vae-and-bnn

fraud detection on the paysim dataset, with the use of VAE to perform data-augmentation and BNN to classify the datapoints.

bayesian-inference bayesian-neural-networks deep-learning fraud-detection probabilistic-programming variational-autoencoder variational-inference

Last synced: 15 Nov 2024

https://github.com/tkusmierczyk/lcvi

Variational Bayesian decision-making for continuous utilities

approximate-inference bayesian-inference decision-making machine-learning pytorch-implementation variational-inference

Last synced: 21 Nov 2024

https://github.com/andersy005/probabilistic-programming-and-bayesian-with-pymc3

Implementation of probabilistic programming and Bayesian algorithms in Python, based on C. Davidson's Bayesian Methods for Hackers

bayesian-inference probabilistic-programming pymc3 python statistical-analysis variational-inference

Last synced: 07 Jan 2025

https://github.com/ngiann/GaussianVariationalInference.jl

Approximate variational inference in Julia

bayesian-inference bayesian-methods julia-language machine-learning posterior-distributions variational-inference

Last synced: 13 Nov 2024

https://github.com/ngiann/gaussianvariationalinference.jl

Approximate variational inference in Julia

bayesian-inference bayesian-methods julia-language machine-learning posterior-distributions variational-inference

Last synced: 12 Oct 2024

https://github.com/gurbaaz27/cs690a-clustering-spatial-transcriptomics-data

Course Assignment on Clustering of Spatial Transcriptomics Data

cancer-genomics clustering computational-biology computational-genomics deep-learning gene-expression k-means-clustering leiden-algorithm louvain-algorithm rna-seq spatial-transcriptomics transcriptomics variational-autoencoder variational-autoencoders variational-inference visium

Last synced: 14 Nov 2024

https://github.com/jbris/nextflow-graph-machine-learning

A Nextflow pipeline demonstrating how to train graph neural networks for gene regulatory network reconstruction using DREAM5 data.

deep-learning docker docker-compose dream5 gene-regulatory-network gene-regulatory-network-inference gene-regulatory-networks graph-neural-network graph-neural-networks graphsage machine-learning minio mlflow mlops nextflow nextflow-pipeline nextflow-pipelines variational-autoencoder variational-inference

Last synced: 13 Nov 2024

https://github.com/jbris/prefect-surrogate-models

Demonstrating the use of Prefect to orchestrate the creation of machine learning surrogate models as applied to mechanistic crop models.

bayesian-optimization botorch dask docker docker-compose dvc gpytorch mechanistic-models minio mlflow mlflow-tracking-server mlops pcse prefect prefect-agent process-modeling surrogate-based-optimization surrogate-models variational-bayes variational-inference

Last synced: 13 Nov 2024

https://github.com/lacerbi/vbmc

Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB (old location)

bayesian-inference data-analysis gaussian-processes machine-learning matlab variational-inference

Last synced: 12 Dec 2024

https://github.com/4ment/phylojax

jax phylogenetics variational-inference

Last synced: 27 Dec 2024

https://github.com/dirmeier/dmvi

Diffusion models for probabilistic programming

diffusion-models jax probabilistic-models probabilistic-programming variational-inference

Last synced: 17 Jan 2025

https://github.com/frankaging/generative-physics-inference

Slip or Not? Unsupervised Learning to Understand Physical Scene Using Multimodal Variational Physics Inference Network

cognitive-services generative-model intuitive-physics multimodal-deep-learning physics-simulation variational-autoencoder variational-inference

Last synced: 10 Jan 2025

https://github.com/slimgroup/reliableavi.jl

Code to partially reproduce results in "Reliable amortized variational inference with physics-based latent distribution correction"

bayesian-inference deep-learning inverse-problems variational-inference

Last synced: 30 Nov 2024

https://github.com/beegass/vaes

Reproducible code showing the various types of variational autoencoders I have implemented

flax flux jax pytorch variational-autoencoder variational-inference

Last synced: 03 Oct 2024

https://github.com/jilljenn/vae

Variational Factorization Machines in TensorFlow and PyTorch

factorization-machines pytorch tensorflow tensorflow-probability torch-distributions variational-inference

Last synced: 25 Nov 2024

https://github.com/soran-ghaderi/torchebm

⚡ Energy-Based Modeling library for PyTorch, offering tools for sampling, inference, and learning in complex distributions.

contrastive-divergence cuda diffusion-models energy-based-model generative-ai langevin-dynamics noise-contrastive-estimation probabilistic-machine-learning reasoning sampling-methods score-matching variational-inference

Last synced: 26 Dec 2024

https://github.com/biaslab/nsi-silverbox

Online system identification in Silverbox by minimising free energy

free-energy-principle harmonic-oscillator system-identification variational-inference

Last synced: 27 Dec 2024

https://github.com/vsimkus/variational-gibbs-inference

[JMLR] Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".

data-science flow gibbs-sampling incomplete-data machine-learning missing-data statistical-model vae variational-inference

Last synced: 19 Jan 2025