EurekAlert!

Heterogeneous spatio-temporal graph contrastive learning for point-of-interest recommendation

As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...
EurekAlert!

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Representation of a Latent Dynamics Network. The neural network consists of two sub-networks: the first (represented at the top of the figure) has the function of predicting the evolution of "latent ...
JSTOR Daily

A Neural Basis for Phonological Awareness? An Oscillatory Temporal-Sampling Perspective

Individual differences in phonological awareness, or speech-sound awareness, between children predict reading and spelling development across languages. Recent advances in our understanding of the ...
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 ...