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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 1501–1510 of 2226 papers

TitleStatusHype
Stochastic triangular mesh mapping: A terrain mapping technique for autonomous mobile robots—0
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction—0
Bayesian Learning-Based Adaptive Control for Safety Critical SystemsCode0
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization—0
Inference of a mesoscopic population model from population spike trainsCode0
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models—0
The Neural Moving Average Model for Scalable Variational Inference of State Space ModelsCode0
Bayesian Graph Convolution LSTM for Skeleton Based Action Recognition—0
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference—0
Non-Gaussian processes and neural networks at finite widths—0
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Benchmark Results

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