Abstract: Activation functions are pivotal in neural networks, determining the output of each neuron. Traditionally, functions like sigmoid and ReLU have been static and deterministic. However, the ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

A new international study has introduced Curved Neural Networks—a new type of AI memory architecture inspired by ideas from geometry. The study shows that bending the "space" in which AI "thinks" can ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations—it's a triumph of your associative memory, in which one piece of information (the first few notes ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

This study presents useful findings on the differences between male and hermaphrodite C. elegans connectomes and how they may result in changes in locomotory behavioural outputs. However, the study ...

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