GpstuffGPstuff - Gaussian process models for Bayesian analysis
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Good PapersI 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
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GpflowGaussian processes in TensorFlow
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BcpdBayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available
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VbmcVariational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
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boundary-gpKnow Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
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DropoutsPyTorch Implementations of Dropout Variants
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autoreparamAutomatic Reparameterisation of Probabilistic Programs
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prosperA Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions
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models-by-exampleBy-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
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GaussianblurAn easy and fast library to apply gaussian blur filter on any images. 🎩
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periodicityUseful tools for periodicity analysis in time series data.
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artificial neural networksA collection of Methods and Models for various architectures of Artificial Neural Networks
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AutoForceSparse Gaussian Process Potentials
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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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Pymc3Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
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noisy-K-FACNatural Gradient, Variational Inference
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Stheno.jlProbabilistic Programming with Gaussian processes in Julia
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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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VINFRepository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
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modelsForecasting 🇫🇷 elections with Bayesian statistics 🥳
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ReactiveMP.jlJulia package for automatic Bayesian inference on a factor graph with reactive message passing
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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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FBNNCode for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
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brunoa deep recurrent model for exchangeable data
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sqairImplementation of Sequential Attend, Infer, Repeat (SQAIR)
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GeorgeFast and flexible Gaussian Process regression in Python
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hyper-enginePython library for Bayesian hyper-parameters optimization
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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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haskell-vaeLearning about Haskell with Variational Autoencoders
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mnist-challengeMy solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
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lgprR-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.
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BayesianoptimizationA Python implementation of global optimization with gaussian processes.
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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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viabelEfficient, lightweight variational inference and approximation bounds
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GPimGaussian processes and Bayesian optimization for images and hyperspectral data
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Ipynotebook machinelearningThis contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
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Universal Head 3DMMThis is a Project Page of 'Towards a complete 3D morphable model of the human head'
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k2scK2 systematics correction using Gaussian processes
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Bayes NnLecture notes on Bayesian deep learning
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random-fourier-featuresImplementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
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active-inferenceA toy model of Friston's active inference in Tensorflow
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lagvaeLagrangian VAE
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PyLDAA Latent Dirichlet Allocation implementation in Python.
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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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Awesome VaesA curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
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CIKM18-LCVACode for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
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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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GPBoostCombining tree-boosting with Gaussian process and mixed effects models
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