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 51–60 of 2226 papers

TitleStatusHype
Bias or Optimality? Disentangling Bayesian Inference and Learning Biases in Human Decision-Making—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching—0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance SpectroscopyCode0
Bayesian Robust Aggregation for Federated LearningCode0
Ensemble Kalman filter for uncertainty in human language comprehension—0
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties—0
Data-driven Approach for Interpolation of Sparse DataCode0
Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges—0
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Benchmark Results

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