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 891–900 of 2226 papers

TitleStatusHype
Amortized Bayesian Inference of GISAXS Data with Normalizing FlowsCode0
Probabilistic Wind Park Power Prediction using Bayesian Deep Learning and Generative Adversarial Networks—0
Generalized second law of thermodynamics in the Glosten-Milgrom model—0
Feature Selection via the Intervened Interpolative Decomposition and its Application in Diversifying Quantitative Strategies—0
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning—0
Hamiltonian Adaptive Importance Sampling—0
Ensemble-based gradient inference for particle methods in optimization and samplingCode0
Batch Bayesian optimisation via density-ratio estimation with guaranteesCode0
Improved Marginal Unbiased Score Expansion (MUSE) via Implicit DifferentiationCode0
Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference—0
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Benchmark Results

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