SOTAVerified

Bayesian Inference

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

Papers

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Showing 1511–1520 of 2226 papers

TitleStatusHype
Hierarchical Bayesian myocardial perfusion quantification—0
Hierarchical MTC User Activity Detection and Channel Estimation with Unknown Spatial Covariance—0
Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs—0
Hierarchical thematic classification of major conference proceedings—0
HIF: Height Interval Filtering for Efficient Dynamic Points Removal—0
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm—0
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling—0
High-Performance FPGA-based Accelerator for Bayesian Neural Networks—0
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models—0
HomeEmergency -- Using Audio to Find and Respond to Emergencies in the Home—0
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Benchmark Results

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