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 1841–1850 of 2226 papers

TitleStatusHype
Bayesian Learning for Neural Networks: an algorithmic survey—0
Bayesian Learning of Kernel Embeddings—0
Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes—0
Bayesian Learning via Neural Schrödinger-Föllmer Flows—0
Bayesian Logistic Shape Model Inference: application to cochlea image segmentation—0
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets—0
Bayesian Low Rank Tensor Ring Model for Image Completion—0
Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias—0
Bayesian mechanics of self-organising systems—0
Bayesian Metaplasticity from Synaptic Uncertainty—0
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Benchmark Results

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