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 521–530 of 2226 papers

TitleStatusHype
Understanding and mitigating difficulties in posterior predictive evaluation—0
Bayesian Online Natural Gradient (BONG)Code0
MAGIC: Modular Auto-encoder for Generalisable Model Inversion with Bias CorrectionsCode0
Kernel Semi-Implicit Variational InferenceCode0
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
Bayesian Inference with Deep Weakly Nonlinear Networks—0
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification—0
A hierarchical Bayesian model for syntactic priming—0
Fast Bayesian Inference for Neutrino Non-Standard Interactions at Dark Matter Direct Detection ExperimentsCode0
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Benchmark Results

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