Frontiers

Spiking Neural Networks at Scale: Learning Algorithms, Architectures, and Real-World Applications

Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
Live Science on MSN

Scientists invent 'Pulse-Fi' prototype — a Wi-Fi heart rate monitor that's cheaper to set up than the best wearable devices

Engineers are in the early stages of harnessing Wi-Fi as a way to monitor heart rates, but don't expect to use your home ...
eLife

Neural dynamics of reversal learning in the prefrontal cortex and recurrent neural networks

The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...
eLife

Neural signatures of motor memories emerge in neural network models

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, public reviews, and a provisional response from the authors. This work investigates ...
Frontiers

Deriving equivalent symbol-based decision models from feedforward neural networks

1 KNDS Deutschland GmbH & Co. KG, Munich, Germany 2 Institute for Software Technology, University of the Bundeswehr Munich, Neubiberg, Germany Artificial intelligence (AI) has emerged as a ...
IEEE

Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
C&EN

PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study introduces PROFIS, a new generative model capable of the design of ...