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Top 65 variational-inference open source projects

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
Probabilistic Models
Collection of probabilistic models and inference algorithms
Awesome Normalizing Flows
A list of awesome resources on normalizing flows.
Variational Inference With Normalizing Flows
Reimplementation of Variational Inference with Normalizing Flows (
Scalable inference for a generative model of astronomical images
Tensorflow Mnist Cvae
Tensorflow implementation of conditional variational auto-encoder for MNIST
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
Bayes By Backprop
PyTorch implementation of "Weight Uncertainty in Neural Networks"
Inverse rl
Adversarial Imitation Via Variational Inverse Reinforcement Learning
Rnn Vae
Variational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"
Gp Infer Net
Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
Variational gradient matching for dynamical systems
Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
Bayesian Neural Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Pytorch Bayesiancnn
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
Bayes Nn
Lecture notes on Bayesian deep learning
Probabilistic unet
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Awesome Vaes
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
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..
Automatic Reparameterisation of Probabilistic Programs
Efficient, lightweight variational inference and approximation bounds
Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (
Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
Julia package for automatic Bayesian inference on a factor graph with reactive message passing
A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
Abstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.
1-60 of 65 variational-inference projects