Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular ...

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development.

Chandler, Arizona – December 15, 2025 – PRESSADVANTAGE – Rainman Consulting LLC, a digital marketing firm based in the ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Biometric technologies, including face and fingerprint recognition, also strengthen identity verification and reduce exposure ...

Not only has Google's Gemini 3 model been trained on the company's own TPUs, but I've been using a MacBook Pro with Apple's ...

Shantanu Kumar ’26, the first student to enroll in SOM’s joint-degree program with the Yale School of Engineering & Applied ...

Graph Neural Networks (GNNs) are reshaping AI by enhancing data interpretation and improving applications. Learn how GNNs are crucial in advancing machine learning models. Graph Neural Networks (GNNs) ...

Cloud migration and application modernization have become make-or-break imperatives for enterprises, yet traditional approaches often stumble under the weight of complexity and legacy systems. Now, ...

Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...