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actuarActuarial functions and heavy tailed distributions for R
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PyLDAA Latent Dirichlet Allocation implementation in Python.
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Mutual labels: variational-inference
boundary-gpKnow Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
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vireoDemultiplexing pooled scRNA-seq data with or without genotype reference
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AI Learning HubAI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
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Awesome Normalizing FlowsA list of awesome resources on normalizing flows.
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BayesByHypernetCode for the paper Implicit Weight Uncertainty in Neural Networks
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ccubeBayesian mixture models for estimating and clustering cancer cell fractions
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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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stan-distributionsA web app to visualize distributions in Stan. Uses Stan Math C++ compiled to Webassembly to evaluate the functions using actual Stan implementations. Uses d3.js for visualizations.
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rssRegression with Summary Statistics.
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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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active-inferenceA toy model of Friston's active inference in Tensorflow
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stanTuneRThis code uses the algebra solver in Stan (https://mc-stan.org/) to find the parameters of a distribution that produce a desired tail behavior.
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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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