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 1731–1740 of 2226 papers

TitleStatusHype
Bayesian Boosting for Linear Mixed Models—0
Bayesian brains and the Rényi divergence—0
Bayesian calibration of differentiable agent-based models—0
Bayesian causal inference via probabilistic program synthesis—0
Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks—0
Bayesian Context Aggregation for Neural Processes—0
Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control—0
Bayesian data fusion with shared priors—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification—0
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Benchmark Results

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