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 1151–1160 of 2226 papers

TitleStatusHype
Transport Quasi-Monte Carlo—0
Tree-Structured Stick Breaking for Hierarchical Data—0
Trust and Time Preference: Measuring a Causal Effect in a Random-Assignment Experiment—0
Tutorial: VAE as an inference paradigm for neuroimaging—0
UAV-Based Remote Sensing of Soil Moisture Across Diverse Land Covers: Validation and Bayesian Uncertainty Characterization—0
Unbiased Bayes for Big Data: Paths of Partial Posteriors—0
Uncertain Evidence in Probabilistic Models and Stochastic Simulators—0
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue—0
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference—0
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift—0
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Benchmark Results

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