Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Abstract: With the boom of machine learning (ML) techniques, software practitioners are building ML systems to process massive volumes of streaming data for diverse software engineering tasks, such as ...
Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...
Amirali Aghazadeh receives funding from Georgia Tech. When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found something astonishing.
You’re managing a federal agency contact center when someone calls in with a bomb threat targeting a government building. The employee immediately begins working to obtain as much information from the ...
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Betting companies train machine learning programs to monitor players’ behaviour. AI technologies seem to have been integrated into every corner of our lives. Most businesses have jumped on the ...
They linger in our water, our blood and the environment—so-called "forever chemicals” that are notoriously difficult to detect. But researchers at the University of Chicago Pritzker School of ...
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