AI sheds light on hard-to-study ocean currents

The Indonesian Throughflow carries both warm water and fresh water from the Pacific into the Indian Ocean. As the only ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
IEEE

Skeleton-Based Action Recognition Using Multibranch Adaptive Graph Convolutional Network With Pose Refinement

Abstract: A multibranch adaptive graph convolutional network is proposed for human action recognition by combining graph convolutional networks (GCNs), adaptive learning, and multibranch feature ...
Quanta Magazine

New Proof Settles Decades-Old Bet About Connected Networks

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...
IEEE

Augmented Graph Convolutional Network for Enhancing Label Reachability

Abstract: Graph Convolutional Networks (GCNs) have emerged as a leading approach for semi-supervised node classification. However, due to the uneven distribution of labeled nodes in graphs, only a ...
EurekAlert!

D2-GCN: a graph convolutional network with dynamic disentanglement for node classification

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
Scientific Research Publishing

Kipf, T.N. and Welling, M. (2017) Semi-Supervised Classification with Graph Convolutional Networks.

ABSTRACT: Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph ...