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 471–480 of 2226 papers

TitleStatusHype
Bayesian calibration of differentiable agent-based models—0
Bayesian inference to improve quality of Retrieval Augmented Generation—0
Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family—0
Bayesian inference via rejection filtering—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—0
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables—0
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method—0
Bayesian Inference with Deep Weakly Nonlinear Networks—0
Bayesian inference with finitely wide neural networks—0
Adaptive Gaussian Copula ABC—0
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Benchmark Results

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