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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 151–160 of 2226 papers

TitleStatusHype
FLORA: Formal Language Model Enables Robust Training-free Zero-shot Object Referring Analysis—0
Tutorial: VAE as an inference paradigm for neuroimaging—0
Distilling Calibration via Conformalized Credal Inference—0
Comparing latent inequality with ordinal data—0
Stable Derivative Free Gaussian Mixture Variational Inference for Bayesian Inverse ProblemsCode2
A Bayesian Approach for Discovering Time- Delayed Differential Equation from Data—0
Adaptive posterior distributions for uncertainty analysis of covariance matrices in Bayesian inversion problems for multioutput signals—0
Generative Emergent Communication: Large Language Model is a Collective World Model—0
Testing and Improving the Robustness of Amortized Bayesian Inference for Cognitive ModelsCode0
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network—0
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Benchmark Results

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