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 121–130 of 2226 papers

TitleStatusHype
Evidence of Replica Symmetry Breaking under the Nishimori conditions in epidemic inference on graphs—0
Bayesian inference from time series of allele frequency data using exact simulation techniques—0
In-Context Parametric Inference: Point or Distribution Estimators?—0
Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreakCode0
Multifidelity Simulation-based Inference for Computationally Expensive Simulators—0
VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR IdentificationCode1
False Discovery Rate Control via Frequentist-assisted Horseshoe—0
Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation—0
Distribution learning via neural differential equations: minimal energy regularization and approximation theory—0
Generalised Bayesian distance-based phylogenetics for the genomics eraCode0
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Benchmark Results

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