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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 2211–2220 of 2226 papers

TitleStatusHype
Perceptual Multistability as Markov Chain Monte Carlo Inference—0
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process—0
A Neural Implementation of the Kalman Filter—0
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations—0
A Bayesian Analysis of Dynamics in Free Recall—0
Analyzing human feature learning as nonparametric Bayesian inference—0
Stochastic Relational Models for Large-scale Dyadic Data using MCMC—0
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes—0
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences—0
Goal-directed decision making in prefrontal cortex: a computational framework—0
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Benchmark Results

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