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 761–770 of 2226 papers

TitleStatusHype
Deep Learning Surrogates for Real-Time Gas Emission Inversion—0
Deep Maxout Network Gaussian Process—0
Deep Network Regularization via Bayesian Inference of Synaptic Connectivity—0
Bayesian Federated Model Compression for Communication and Computation Efficiency—0
Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields—0
Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints—0
A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics—0
Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
Bayesian Flow Networks in Continual Learning—0
Biases and Variability from Costly Bayesian Inference—0
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Benchmark Results

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