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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 1921–1930 of 2226 papers

TitleStatusHype
Bayesian inference on random simple graphs with power law degree distributions—0
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable CouplingsCode0
Linear, Machine Learning and Probabilistic Approaches for Time Series Analysis—0
The Stochastic complexity of spin models: Are pairwise models really simple?—0
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence ClusteringCode0
Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment—0
Bone fusion in normal and pathological development is constrained by the network architecture of the human skull—0
Adversarial Message Passing For Graphical Models—0
Expectation Propagation performs a smoothed gradient descent—0
A Probabilistic Model of Social Decision Making based on Reward Maximization—0
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Benchmark Results

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