SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 661–670 of 2226 papers

TitleStatusHype
Bayesian inference with finitely wide neural networks—0
Calibrating Transformers via Sparse Gaussian ProcessesCode1
Eryn : A multi-purpose sampler for Bayesian inferenceCode1
Bayesian Posterior Perturbation Analysis with Integral Probability Metrics—0
Joint Task and Data Oriented Semantic Communications: A Deep Separate Source-channel Coding Scheme—0
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference—0
Deep Learning Enhanced Realized GARCHCode0
Parameters for > 300 million Gaia stars: Bayesian inference vs. machine learning—0
Event Temporal Relation Extraction with Bayesian Translational Model—0
Bayesian Non-parametric Hidden Markov Model for Agile Radar Pulse Sequences Streaming Analysis—0
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Benchmark Results

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