Bayesian Inference
Bayes' Theorem allows a program to infer the probabilities of likely causes from the probabilities of their effects, when what it is given are the probabilities of effects, given the causes.
SparseBayesianGenerativeModeling forCompressiveSensing
Neural Information Processing Systems
It then serves as probabilistic prior to regularize the inverse problem(1).
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Estimating the Rate-Distortion Function by Wasserstein Gradient Descent Yibo Yang 1 Stephan Eckstein 2 Marcel Nutz 3 Stephan Mandt 1 1
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In this work, we propose a new approach to R-D estimation from the perspective of optimal transport.
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Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
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Our experiments show that Genfer is often faster than the existing exact inference tools PSI, Dice, and Prodigy.
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