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 1231–1240 of 2226 papers

TitleStatusHype
A Bayesian Approach to Identifying Representational Errors—0
W2WNet: a two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality—0
Adaptive Degradation Process with Deep Learning-Driven Trajectory—0
Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Development—0
Sparse Algorithms for Markovian Gaussian ProcessesCode0
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms—0
A New Parameterized Family of Stochastic Particle Flow Filters—0
Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks—0
A hierarchical Bayesian model to find brain-behaviour associations in incomplete data setsCode0
Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs—0
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Benchmark Results

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