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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 231–240 of 2226 papers

TitleStatusHype
Surprise Calibration for Better In-Context Learning—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
Real-World Deployment of a Lane Change Prediction Architecture Based on Knowledge Graph Embeddings and Bayesian Inference—0
Foundation Models for Causal Inference via Prior-Data Fitted Networks—0
Bayesian Probabilistic Matrix Factorization—0
Textual Bayes: Quantifying Uncertainty in LLM-Based Systems—0
Bayesian Inverse Physics for Neuro-Symbolic Robot Learning—0
Stability of Mean-Field Variational Inference—0
ALINE: Joint Amortization for Bayesian Inference and Active Data AcquisitionCode0
Variational Inference for Quantum HyperNetworks—0
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Benchmark Results

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