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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 731–740 of 2226 papers

TitleStatusHype
Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields—0
Adaptive mitigation of time-varying quantum noise—0
Bayesian deep learning framework for uncertainty quantification in high dimensions—0
Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline—0
A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics—0
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo—0
Bottom-up data integration in polymer models of chromatin organisation—0
Bridging Privacy and Robustness for Trustworthy Machine Learning—0
Device Detection and Channel Estimation in MTC with Correlated Activity Pattern—0
Biases and Variability from Costly Bayesian Inference—0
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Benchmark Results

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