SOTAVerified

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
A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process—0
Accelerated physical emulation of Bayesian inference in spiking neural networks—0
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)Code1
Understanding and Accelerating Particle-Based Variational InferenceCode1
Scalable approximate Bayesian inference for particle tracking dataCode0
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)—0
Rating Distributions and Bayesian Inference: Enhancing Cognitive Models of Spatial Language Use—0
An Introduction to Animal Movement Modeling with Hidden Markov Models using Stan for Bayesian Inference—0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology—0
Random Feature Stein DiscrepanciesCode0
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Benchmark Results

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