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 1071–1080 of 2226 papers

TitleStatusHype
On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks—0
Active Inference in Robotics and Artificial Agents: Survey and Challenges—0
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems—0
A sampling-based circuit for optimal decision making—0
Sampling with Trusthworthy Constraints: A Variational Gradient FrameworkCode0
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation—0
A Novel Gaussian Process Based Ground Segmentation Algorithm with Local-Smoothness Estimation—0
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random FeaturesCode0
BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained DomainCode0
Impression learning: Online representation learning with synaptic plasticityCode0
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Benchmark Results

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