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 951–960 of 2226 papers

TitleStatusHype
Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations—0
PAVI: Plate-Amortized Variational Inference—0
On the safe use of prior densities for Bayesian model selection—0
BInGo: Bayesian Intrinsic Groupwise Registration via Explicit Hierarchical Disentanglement—0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference—0
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees—0
Functional Ensemble DistillationCode0
Information Threshold, Bayesian Inference and Decision-Making—0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
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Benchmark Results

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