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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 1401–1410 of 2226 papers

TitleStatusHype
Fast Burst-Sparsity Learning Approach for Massive MIMO-OTFS Channel Estimation—0
Fast Convergence for Langevin Diffusion with Manifold Structure—0
Fast Convergence for Langevin with Matrix Manifold Structure—0
Fast Dual Variational Inference for Non-Conjugate LGMs—0
Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk—0
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows—0
Fast Low-Rank Bayesian Matrix Completion with Hierarchical Gaussian Prior Models—0
Fast online inference for nonlinear contextual bandit based on Generative Adversarial Network—0
Fast Parallel SVM using Data Augmentation—0
Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes—0
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Benchmark Results

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