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 321–330 of 2226 papers

TitleStatusHype
Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors—0
Is In-Context Learning in Large Language Models Bayesian? A Martingale PerspectiveCode0
Logistic Variational Bayes RevisitedCode0
Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noiseCode0
Bayesian Online Natural Gradient (BONG)Code0
Understanding and mitigating difficulties in posterior predictive evaluation—0
Kernel Semi-Implicit Variational InferenceCode0
MAGIC: Modular Auto-encoder for Generalisable Model Inversion with Bias CorrectionsCode0
Deterministic and statistical calibration of constitutive models from full-field data with parametric physics-informed neural networks—0
Infinite-dimensional Diffusion Bridge Simulation via Operator LearningCode0
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Benchmark Results

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