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 71–80 of 2226 papers

TitleStatusHype
Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations—0
Power-scaled Bayesian Inference with Score-based Generative Models—0
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biologyCode0
Uncertainty Propagation in the Fast Fourier TransformCode0
Metropolis-Hastings Captioning Game: Knowledge Fusion of Vision Language Models via Decentralized Bayesian Inference—0
Advancing Autonomous Vehicle Safety: A Combined Fault Tree Analysis and Bayesian Network Approach—0
Programs as Singularities—0
Stacking Variational Bayesian Monte Carlo—0
The challenge of uncertainty quantification of large language models in medicine—0
Probabilistic Position-Aided Beam Selection for mmWave MIMO Systems—0
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Benchmark Results

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