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 1581–1590 of 2226 papers

TitleStatusHype
A hybrid tau-leap for simulating chemical kinetics with applications to parameter estimation—0
AI and extreme scale computing to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers—0
AI-Powered Bayesian Inference—0
A Kernel Learning Method for Backward SDE Filter—0
A Kolmogorov-Smirnov test for the molecular clock on Bayesian ensembles of phylogenies—0
A Latent Space Theory for Emergent Abilities in Large Language Models—0
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees—0
Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions—0
Algorithms of the LDA model [REPORT]—0
Aligned Multi-Task Gaussian Process—0
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Benchmark Results

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