Federated learning (FL) has emerged as a popular machine learning paradigm which allows multiple data owners to train models collaboratively with out sharing their raw datasets. It holds potential for ...

A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute.

Machine learning-based neural network potentials often cannot describe long-range interactions. Here the authors present an approach for building neural network potentials that can describe the ...

A Cornell research group led by Prof. Peter McMahon, applied and engineering physics,has successfully trained various physical systems to perform machine learning computations in the same way as a ...

SANTA CLARA, Calif.--(BUSINESS WIRE)-- What’s New: Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future ...

A basic knowledge of programming in Python, Julia or MATLAB. A basic knowledge of probability theory and of differential equations. This unit will introduce the neuronal dynamics supporting biological ...

SANTA CLARA, Calif.--(BUSINESS WIRE)--What’s New: Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future ...