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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1591–1600 of 2226 papers

TitleStatusHype
Alternating linear scheme in a Bayesian framework for low-rank tensor approximation—0
A majorization-minimization algorithm for nonnegative binary matrix factorization—0
A Markov Model of Machine Translation using Non-parametric Bayesian Inference—0
A Mathematical Trust Algebra for International Nation Relations Computation and Evaluation—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression—0
Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning—0
Variational inference of fractional Brownian motion with linear computational complexity—0
Amortized Bayesian Inference for Models of Cognition—0
Amortized Bayesian Mixture Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified