Tag: uncertainty quantification

A new leakage-audited benchmark shows that random data splitting inflates toxicity model performance by up to 0.079 AUROC points while ...

George Mason University's Edward Oughton will lead a $499,837 NSF-funded collaboration to build an AI-enabled, uncertainty-aware framework linking space weather ...

A new evidence map of 126 studies shows artificial intelligence can accelerate PFAS toxicology and risk assessment, but only when ...

A new study of ensemble deep learning on medical image benchmarks shows that the most accurate models are rarely the ...

Researchers have extended a high-fidelity voltage stability index into a probabilistic framework that quantifies collapse probability, confidence bounds and risk-based ...

Rice University and Cornell statisticians have developed a Bayesian method called BMRR that combines conflicting sports rankings, quantifies uncertainty, and ...

A global systematic review of 73 studies finds that artificial intelligence is highly effective at short-term coastal hazard forecasting but ...

University of Washington researchers have built a decision support system that combines PET imaging, immune repertoire sequencing, and blood cytokines ...

Researchers in India report that a fuzzy logic-driven dynamic clustering algorithm outperformed standard machine learning methods on brain tumor data, ...

Researchers in Shanghai have developed TECL, a machine learning framework that treats conflicting opinions across multiple data views as valuable ...