In today's machine learning field, deep neural network models are becoming increasingly large and complex, posing significant challenges to traditional electronic computing hardware. To address this ...

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...

University of Arizona researchers have demonstrated that multiphoton microscopy (MPM), combined with machine learning and deep learning techniques, can accurately distinguish pancreatic neuroendocrine ...

In research that could improve weather forecasting and winter driving safety, a University of Michigan-led study ...

With increase in the applications of autonomous systems, in both civilian and military domains, it has become increasingly ...

A research team has developed a powerful unsupervised deep learning network that can accurately separate wood and leaf ...

Understanding the neural mechanisms underlying associative threat learning is essential for advancing behavioral models of threat and adaptation. We investigated distinct activation patterns across ...

Research on complex nonequilibrium processes and nonlinear dynamics has seen remarkable growth, revealing rich behavior across classical and quantum ...

Explore the relationship between wildlife, habitats, and human impacts. Focus on wildlife management, conservation, and policy topics. At Michigan Tech, our master's in wildlife ecology and ...