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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 741–750 of 2226 papers

TitleStatusHype
Sparse species interactions reproduce abundance correlation patterns in microbial communities—0
A Bayesian sparse factor model with adaptive posterior concentration—0
Bayesian inference and neural estimation of acoustic wave propagation—0
Improving Neural Additive Models with Bayesian PrinciplesCode0
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty—0
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks—0
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo AlgorithmsCode0
Adversarial robustness of amortized Bayesian inferenceCode0
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior InferenceCode0
Bayesian calibration of differentiable agent-based models—0
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Benchmark Results

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