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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 1751–1760 of 2226 papers

TitleStatusHype
Empirical analysis of representation learning and exploration in neural kernel banditsCode0
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interactionCode0
Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing ConstantsCode0
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning AlgorithmsCode0
Bayesian Calibration of Win Rate Estimation with LLM EvaluatorsCode0
Amortized Bayesian inference for clustering modelsCode0
Likelihood-free inference with emulator networksCode0
Differentially Private Bayesian Inference for Exponential FamiliesCode0
Accelerated Bayesian imaging by relaxed proximal-point Langevin samplingCode0
Differentially Private Bayesian Learning on Distributed DataCode0
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Benchmark Results

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