SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Showing 20512060 of 2226 papers

TitleStatusHype
Bayesian Inference for Neighborhood Filters With Application in Denoising0
Real-Time Part-Based Visual Tracking via Adaptive Correlation Filters0
A Bounded p-norm Approximation of Max-Convolution for Sub-Quadratic Bayesian Inference on Additive Factors0
Weight Uncertainty in Neural NetworksCode1
Salient Structure Detection by Context-Guided Visual Search0
On Markov chain Monte Carlo methods for tall dataCode0
Formalizing Preference Utilitarianism in Physical World Models0
Network Plasticity as Bayesian InferenceCode0
A closed-form approach to Bayesian inference in tree-structured graphical models0
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series0
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Benchmark Results

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