A University of Idaho lab received $1.3 million from the Department of Defense to study early detection methods for ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

Are you contemplating a PhD and interested in economic or social science applications of machine learning? You might be a good fit for our pre-doc position. The Center for Applied Artificial ...

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

A decorated UVA engineer collects early-career honors for his leadership and contributions to the data mining field.

If nonliving materials can produce rich, organized mixtures of organic molecules, then the traditional signs we use to ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

At the world’s largest artificial-intelligence conference, known as NeurIPS, Weichen Huang almost blended in. Last month in Vancouver, he was one of numerous researchers explaining their ...