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 1691–1700 of 2226 papers

TitleStatusHype
Meta Architecture SearchCode0
Surrogate-assisted Bayesian inversion for landscape and basin evolution modelsCode0
Probabilistic Model Checking of Robots Deployed in Extreme Environments—0
Physics-Based Learning for Robotic Environmental Sensing—0
Sampling-based Bayesian Inference with gradient uncertainty—0
Efficient transfer learning and online adaptation with latent variable models for continuous control—0
That's Mine! Learning Ownership Relations and Norms for Robots—0
Predictive Approximate Bayesian Computation via Saddle Points—0
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues—0
Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs—0
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Benchmark Results

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