Nature

Temporal Graphs and Dynamic Networks

Temporal graphs serve as a powerful framework for representing networks whose connections evolve over time. By incorporating time‐stamped interactions, these models capture the dynamic nature of ...

Visual awareness study unlocks interplay between attention and consciousness

A new study led by Dr. Jiang Yi from the Institute of Psychology of the Chinese Academy of Sciences has revealed the first ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Scientific Research Publishing

Reinforcement Learning for Antidepressant Dose Adjustment: An Explainable Agent Approach ()

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...