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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 1001–1010 of 2226 papers

TitleStatusHype
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets—0
Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching—0
Flexible and Hierarchical Prior for Bayesian Nonnegative Matrix Factorization—0
Flexible Bayesian Inference on Partially Observed Epidemics—0
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles—0
Flexible Mixture Modeling on Constrained Spaces—0
Fundamental Linear Algebra Problem of Gaussian Inference—0
FLORA: Formal Language Model Enables Robust Training-free Zero-shot Object Referring Analysis—0
Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model—0
A theory of data variability in Neural Network Bayesian inference—0
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Benchmark Results

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