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 1151–1160 of 2226 papers

TitleStatusHype
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters—0
Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference—0
Recent advances in deep learning theory—0
Recent methods from statistical inference and machine learning to improve integrative modeling of macromolecular assemblies—0
Recent Progress in Image Deblurring—0
Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively—0
Reconstructing networks with unknown and heterogeneous errors—0
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference—0
Recovering Latent Signals from a Mixture of Measurements using a Gaussian Process Prior—0
Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo—0
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Benchmark Results

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