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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 1651–1675 of 2226 papers

TitleStatusHype
A prediction rigidity formalism for low-cost uncertainties in trained neural networks—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology—0
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method—0
A Probabilistic Model for Canonicalizing Named Entity Mentions—0
A Probabilistic Model of Social Decision Making based on Reward Maximization—0
A Probabilistic Semi-Supervised Approach with Triplet Markov Chains—0
A rational decision making framework for inhibitory control—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
A Relaxed Drift Diffusion Model for Phylogenetic Trait Evolution—0
Are low frequency macroeconomic variables important for high frequency electricity prices?—0
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation—0
A Review of Change of Variable Formulas for Generative Modeling—0
A Review of Multiple Try MCMC algorithms for Signal Processing—0
Are you using test log-likelihood correctly?—0
Array Partitioning Based Near-Field Attitude and Location Estimation—0
A sampling-based circuit for optimal decision making—0
A Scalable Inference Method For Large Dynamic Economic Systems—0
Score Operator Newton transport—0
A Search and Detection Autonomous Drone System: from Design to Implementation—0
A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems—0
A Simple Generative Model of Logical Reasoning and Statistical Learning—0
A Simulated Annealing Approach to Bayesian Inference—0
Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles—0
Assessing the Impact of Vaccination on Rotavirus Transmission Dynamics Using Bayesian Inference—0
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Benchmark Results

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