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Scientists develop new mathematical model for transfer learning in neural networks

Alessandro Ingrosso, researcher at the Donders Institute for Neuroscience, has developed a new mathematical method in collaboration with colleagues in two Italian research institutions, which enables ...
Science Daily

Synchronization in neural nets: Mathematical insight into neuron readout drives significant improvements in prediction accuracy

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...
Electronic Design

A Neural-Network-Based Approach to Smarter DPD Engines

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.
eLife

Inside Discovery: Where theory meets biology

Veronika Koren talks about pursuing a theory of neural coding that doesn’t fit a simple narrative, and the resilience it took to see it through.
Smithsonian Magazine

Scientists Who Developed the Building Blocks of Artificial Intelligence Win Nobel Prize in Physics

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their work on artificial neural networks and machine learning. Jonathan Nackstrand / AFP via Getty Images A pair of scientists—John ...
The Conversation

Physics Nobel awarded to neural network pioneers who laid foundations for AI

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...