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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 711–720 of 2226 papers

TitleStatusHype
Double Robust Bayesian Inference on Average Treatment Effects—0
A Search and Detection Autonomous Drone System: from Design to Implementation—0
Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data—0
Looking at the posterior: accuracy and uncertainty of neural-network predictions—0
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive ModelsCode1
Few-shot Non-line-of-sight Imaging with Signal-surface Collaborative Regularization—0
Bayesian Learning for Neural Networks: an algorithmic survey—0
Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation—0
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World SurveillanceCode1
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventionsCode0
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Benchmark Results

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