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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 1051–1060 of 2226 papers

TitleStatusHype
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
Structured Stochastic Gradient MCMCCode0
Mismatched Estimation of rank-one symmetric matrices under Gaussian noiseCode0
Compressed Monte Carlo with application in particle filtering—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Hybrid Bayesian Neural Networks with Functional Probabilistic Layers—0
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All NetworksCode1
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
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Benchmark Results

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