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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 1151–1160 of 2226 papers

TitleStatusHype
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
Mismatched Estimation of rank-one symmetric matrices under Gaussian noiseCode0
Structured Stochastic Gradient MCMCCode0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Compressed Monte Carlo with application in particle filtering—0
Hybrid Bayesian Neural Networks with Functional Probabilistic Layers—0
Bayesian brains and the Rényi divergence—0
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty—0
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential EquationsCode0
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks—0
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Benchmark Results

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