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Regression on UCI House electric

Regression on UCI House electric

15.8Training Time (s)FM-GP

Updated 5mo ago

Evaluation results

Method	Links
FM-GP2026.05		15.8
Var2026.05		29.2
GPnn2026.05		36.8

State-of-the-art paper

FM-GP

Scalable Gaussian process inference via neural feature maps

Dataset

UCI House electric

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Related benchmarks

Classification on MNIST (Error Rate, ECE)Classification on CIFAR10 (Error rate, ECE)Training Time on UCI Eeg Classification on UCI Htru2 Classification on UCI Letter

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