Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

The diagram illustrates the interplay among data acquisition, machine learning, and experiment synthesis. Physical models such as thermodynamics and kinetics can be integrated into ML models as ...

A research team led by Prof. Mao Miaohua at the Yantai Institute of Coastal Zone Research of the Chinese Academy of Sciences, ...

Cardiac fibroblasts (CF) can become activated and produce excessive extracellular matrix, contributing to fibrotic remodeling ...

“[T]he only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment.” – CAFC The U.S. Court of Appeals for the Federal Circuit ...

Scientists developed a machine-learning tool that can teach itself, with minimal external guidance, to differentiate between ...

Machine Design’s audience has a diverse familiarity with AI, but one thing is clear—its impact is growing, from streamlining ...

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...

Jim Bobreski of Penn Yan is a process control engineer in power production for 43 years. He also is the author of “Alternate ...

Researchers create an iontronic artificial skin that senses pressure, temperature, and current while learning patterns ...

Researchers at UT Southwestern developed an AI model that uses histopathological slide images to predict which kidney cancer patients will benefit from anti-angiogenic therapy. This deep learning ...