output
20092023
most citedBinary Neural Networks: A Survey

553 citations

Showing cs.LGShow all

5 papers · 1 filter

cs.LG2022★ 107 cited

STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction

Jiahao Ji, Jingyuan Wang, Zhe Jiang +2

High-performance traffic flow prediction model designing, a core technology of Intelligent Transportation System, is a long-standing but still challenging task for industrial and a…

cs.LG2020★ 57 cited

Bi-GCN: Binary Graph Convolutional Network

Junfu Wang, Yunhong Wang, Zhen Yang +2

Graph Neural Networks (GNNs) have achieved tremendous success in graph representation learning. Unfortunately, current GNNs usually rely on loading the entire attributed graph into…

cs.LG2019★ 15 cited

Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction

Lingbo Liu, Jiajie Zhen, Guanbin Li +4

As a crucial component in intelligent transportation systems, traffic flow prediction has recently attracted widespread research interest in the field of artificial intelligence (A…

cs.LG2018★ 8 cited

Graph Convolutional Neural Networks via Motif-based Attention

Hao Peng, Jianxin Li, Qiran Gong +3

Many real-world problems can be represented as graph-based learning problems. In this paper, we propose a novel framework for learning spatial and attentional convolution neural ne…

cs.LG2016★ 82 cited

On the representation and embedding of knowledge bases beyond binary relations

Jianfeng Wen, Jianxin Li, Yongyi Mao +2

The models developed to date for knowledge base embedding are all based on the assumption that the relations contained in knowledge bases are binary. For the training and testing o…