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 241–250 of 2226 papers

TitleStatusHype
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity—0
Multilevel neural simulation-based inferenceCode0
UAV-Based Remote Sensing of Soil Moisture Across Diverse Land Covers: Validation and Bayesian Uncertainty Characterization—0
Amortized variational transdimensional inferenceCode0
Variational Inference for Latent Variable Models in High Dimensions—0
A Group-Wise Narrow Beam Design for Uplink Channel Estimation in Hybrid Beamforming Systems—0
Joint Activity Detection and Channel Estimation for Massive Connectivity: Where Message Passing Meets Score-Based Generative Priors—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
Model Informed Flows for Bayesian Inference of Probabilistic Programs—0
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs—0
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Benchmark Results

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