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 251–260 of 2226 papers

TitleStatusHype
Weakly-supervised Localization of Manipulated Image Regions Using Multi-resolution Learned Features—0
Position: The Future of Bayesian Prediction Is Prior-Fitted—0
Judging LLMs on a Simplex—0
TabPFN: One Model to Rule Them All?Code0
Bayesian Deep Learning for Discrete Choice—0
Generalized Power Priors for Improved Bayesian Inference with Historical Data—0
Inter-Subject Variance Transfer Learning for EMG Pattern Classification Based on Bayesian Inference—0
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation—0
Compositional amortized inference for large-scale hierarchical Bayesian models—0
Understanding Task Representations in Neural Networks via Bayesian Ablation—0
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Benchmark Results

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