Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, ...

Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...

This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...

People can think, behave and function very differently. These observed differences are known to be the result of complex ...

By implementing an automated 3D cell segmentation process, researchers mapped neurons and muscle fibers at the single-cell ...

Devi Parikh, a former senior director of GenAI at Meta-turned co-CEO of an AI company, said you don't need a Ph.D. to do ...

The Navier–Stokes partial differential equation was developed in the early 19th century by Claude-Louis Navier and George ...

Using an AI-supported model developed in-house, an interdisciplinary team at TU Graz has sought new methods to enhance the ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...