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93 search results found

So Vits Svc ⭐ 20,615

SoftVC VITS Singing Voice Conversion

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

Awesome Normalizing Flows ⭐ 1,232

Awesome resources on normalizing flows.

Pytorch Bayesiancnn ⭐ 1,181

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

Normalizing Flows ⭐ 520

PyTorch implementation of normalizing flow models

Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"

Bayesian Torch ⭐ 396

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

Pyvarinf ⭐ 300

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

Autoencoding_vi_for_topic_models ⭐ 211

Tensorflow implementation for prodLDA and NVLDA.

Probabilistic Models ⭐ 196

Collection of probabilistic models and inference algorithms

Icml2015_papers ⭐ 143

Links to ICML 2015 papers available on arxiv

Tensorflow Mnist Cvae ⭐ 134

Tensorflow implementation of conditional variational auto-encoder for MNIST

Noisynaturalgradient ⭐ 115

Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"

Variational Inference With Normalizing Flows ⭐ 106

Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)

PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python

Python implementation of 'Scalable Recommendation with Hierarchical Poisson Factorization'.

Tf Var Attention ⭐ 55

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

Pysvihmm ⭐ 51

Implementation of stochastic variational inference for Bayesian hidden Markov models.

Topic Rnn ⭐ 47

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

Vib Pytorch ⭐ 46

Pytorch implementation of Deep Variational Information Bottleneck

A Latent Dirichlet Allocation implementation in Python.

Variational inference for hierarchical dynamical systems

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

Amortized Inference for Causal Structure Learning, NeurIPS 2022

DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021

Artificial_neural_networks ⭐ 35

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

Efficient, lightweight variational inference and approximation bounds

Mixed-curvature Variational Autoencoders (ICLR 2020)

Ladder Vae Pytorch ⭐ 31

Ladder Variational Autoencoders (LVAE) in PyTorch

Brancher ⭐ 31

A python library for stochastic variational inference and differentiable probabilistic programming

Vae Style Transfer ⭐ 30

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

Variational Inference in Gaussian Mixture Model

Deep Active Inference Mc ⭐ 28

Deep active inference agents using Monte-Carlo methods

Bayes_nn ⭐ 27

Uncertainty interpretations of the neural network

Code for AutoGP

Variational Graph Recurrent Neural Networks - PyTorch

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

Pt Avitm ⭐ 23

PyTorch implementation of AVITM (Autoencoding Variational Inference For Topic Models)

Neural Net Matrix Factorization ⭐ 22

Exploring neural networks (and variational inference) for collaborative filtering

Causalskilllearning ⭐ 21

Codebase for project about unsupervised skill learning via variational inference and causality.

Gradient Boosted Normalizing Flows ⭐ 21

We got a stew going!

[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation

Deep_variational_information_bottleneck ⭐ 20

Tensorflow implementation of deep variational information bottleneck

Autoreparam ⭐ 20

Automatic Reparameterisation of Probabilistic Programs

Graph Generation Vi ⭐ 19

This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation"

Graphbtm ⭐ 19

Code for paper "GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model". Under preparation.

Official repository for the paper TRIDENT: Transductive Decoupled Variational Inference for Few Shot Classification

Implementation of "Variational Inference for Monte Carlo Objectives"

Pytorch Implementation of OpenAI's "Improved Variational Inference with Inverse Autoregressive Flow"

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

Adaptive F Divergence ⭐ 16

A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"

Variational inference for Dirichlet process mixture models with multinomial mixture components.

Hypocentral earthquake location using Stein-variational gradient descent and deep neural network travel-time formulations

Zhusuan Pytorch ⭐ 14

An Elegant Library for Bayesian Deep Learning in PyTorch

A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions

Examples for variational inference

Torch Reparametrised Mixture Distribution ⭐ 14

PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.

A toolbox for inference of mixture models

Ouijaflow ⭐ 13

Probabilistic single-cell pseudotime with Edward+Tensorflow

Cifar 10 Uncertainty ⭐ 12

Cikm18 Lcva ⭐ 12

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

Sentencemim Demo ⭐ 11

This repo contains code to reproduce some of the results presented in the paper "SentenceMIM: A Latent Variable Language Model"

Minimal Gaussian process library in JAX with a simple (custom) approach to state management.

Software to perform multi-ancestry SNP fine-mapping on molecular data

Variational Diffusion Models ⭐ 11

PyTorch implementation of Variational Diffusion Models.

Binary Vae ⭐ 11

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

Variational Interpretable Concept Embeddings

Gmm Em Vb ⭐ 10

This repository is for sharing the scripts of EM algorithm and variational bayes.

Vi_normal ⭐ 10

Variational Inference for a Normal Distribution

Code for "MIM: Mutual Information Machine" paper.

A Probabilistic Framework for Visual Localization in Ambiguous Scenes

[NeurIPS'18] Discrete relaxation of continuous variables for tractable variational inference

Bayesiannn ⭐ 9

Implementing a bayesian neural network in TensorFlow

Attend Infer Repeat Pytorch ⭐ 9

Attend Infer Repeat (AIR) in PyTorch

Deep_learning_onboarding ⭐ 8

List of resources for deep learning

Pytorchavitm ⭐ 8

PyTorch Implementation of Autoencoding Variational Inference for Topic Models (Srivastava and Sutton 2017)

Sparsegpax ⭐ 6

An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.

Vae Tensorflow ⭐ 6

TensorFlow implementation of Auto-Encoding Variational Bayes.

Implementation of Stein Variational Gradient Descent with TensorFlow 2.0

In Depth Vi Tutorial ⭐ 6

(AIWAE) Improving importance weighted auto-encoders with annealed importance sampling

VIMCO in tensorflow.

Generative ⭐ 5

Repository to explore Generative Models

Diverse_sampling ⭐ 5

Official project of DiverseSampling (ACMMM2022 Paper)

Variational Inference On Mnist ⭐ 5

A list of variational inference algorithms and their performance on MNIST

Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)

Code accompanying the Importance Weighted Hierarchical Variational Inference (NeurIPS 2019) paper

Pymc Advi Hmc Demo ⭐ 5

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

Antithetic Vae Public ⭐ 5

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

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