A new study utilizes compact neural networks to uncover the underlying mechanisms behind human decision-making. Scientists have long studied how people and animals make decisions, often looking at how ...

To address this problem, we use the multi-head self-attention mechanism to establish a hybrid model integrating static and dynamic spatial correlation neural network (SDSCNN) for traffic flow ...

Mechanistic interpretability is emerging as a strategic advantage for businesses looking to deploy AI responsibly.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Discover how Google DeepMind is using video games and generative AI to train advanced artificial intelligence for real-world applications.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

"We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture ... to test ...

New research highlights how astrocytes, long considered mere support cells, actively shape brain network dynamics.

Long overlooked and underestimated, glial cells—non-neuronal cells that support, protect and communicate with neurons—are ...

Neuromorphic computing, as a novel approach to processing information by mimicking biological neural networks, has gradually demonstrated significant ...

Using the analogy of the interconnected neural pathways in the brain, network leadership is about harnessing connections to ...

Floods are some of the most devastating natural disasters communities in the United States face, causing billions of dollars ...