Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

Smart home devices market is set for remarkable growth, expected to reach USD 1,590.9 billion by 2034, up from USD 121.8 ...

Explore how machine learning is revolutionising interstitial lung disease management, enhancing early diagnosis, treatment, ...

AI Statisitcs: market size valued at USD 391.70 bn in 2024 and is projected to reach approximately USD 10,173 bn by 2034, at ...

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

We present an integrated approach to derive multimodal MRI markers of cognition that can be transdiagnostically linked to psychopathology. This demonstrates that the predictive ability of neural ...

The XIAOML Kit is one of the devkits that complements Harvard University Professor Vijay Janapa Reddi’s book “Introduction to Machine Learning Systems“, available for free as a 2050-page PDF file. The ...

Predictive machine learning (ML), such as deep learning, excels at pattern recognition tasks like self-driving cars, protein structure prediction, or large language models. However, these models ...

Abstract: Recently, bilevel optimization (BLO) has taken center stage in some very exciting developments in the area of signal processing (SP) and machine learning (ML). Roughly speaking, BLO is a ...

Department of Physics, University of Warwick, Coventry CV4 7AL, U.K. Warwick Centre for Predictive Modelling, School of Engineering, University of Warwick, Coventry CV4 7AL, U.K. You are free to share ...