VINFRepository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
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Pytorch BayesiancnnBayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
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CIKM18-LCVACode for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
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AI Learning HubAI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
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PyroDeep universal probabilistic programming with Python and PyTorch
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prosperA Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
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KvaeKalman Variational Auto-Encoder
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PyLDAA Latent Dirichlet Allocation implementation in Python.
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Probabilistic unetA U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
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normalizing-flowsPyTorch implementation of normalizing flow models
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Rnn VaeVariational Autoencoder with Recurrent Neural Network based on Google DeepMind's "DRAW: A Recurrent Neural Network For Image Generation"
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Bayes By BackpropPyTorch implementation of "Weight Uncertainty in Neural Networks"
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Bayesian Neural NetworksPytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
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probai-2021-pyroRepo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
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Celeste.jlScalable inference for a generative model of astronomical images
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ReactiveMP.jlJulia package for automatic Bayesian inference on a factor graph with reactive message passing
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Pymc3Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
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SelSumAbstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.
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GpflowGaussian processes in TensorFlow
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ccubeBayesian mixture models for estimating and clustering cancer cell fractions
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ProbregPython package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)
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viabelEfficient, lightweight variational inference and approximation bounds
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SIVIUsing neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)
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Deepbayes 2018Seminars DeepBayes Summer School 2018
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lagvaeLagrangian VAE
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VbmcVariational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
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cmdstanrCmdStanR: the R interface to CmdStan
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Gp Infer NetScalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
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sqairImplementation of Sequential Attend, Infer, Repeat (SQAIR)
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DropoutsPyTorch Implementations of Dropout Variants
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haskell-vaeLearning about Haskell with Variational Autoencoders
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BcpdBayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
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noisy-K-FACNatural Gradient, Variational Inference
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Variational AutoencoderVariational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
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artificial neural networksA collection of Methods and Models for various architectures of Artificial Neural Networks
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BayesByHypernetCode for the paper Implicit Weight Uncertainty in Neural Networks
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active-inferenceA toy model of Friston's active inference in Tensorflow
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GpstuffGPstuff - Gaussian process models for Bayesian analysis
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adaptive-f-divergenceA tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
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Bayes NnLecture notes on Bayesian deep learning
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rssRegression with Summary Statistics.
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Tensorflow Mnist CvaeTensorflow implementation of conditional variational auto-encoder for MNIST
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DUNCode for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
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Awesome VaesA curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
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vireoDemultiplexing pooled scRNA-seq data with or without genotype reference
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MxfusionModular Probabilistic Programming on MXNet
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Generative models tutorial with demoGenerative 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..
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Inverse rlAdversarial Imitation Via Variational Inverse Reinforcement Learning
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autoreparamAutomatic Reparameterisation of Probabilistic Programs
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