116 citations · 289 across the 8 of their papers we have counts for
6 papers · 1 filter
WRENCH: A Comprehensive Benchmark for Weak Supervision
Jieyu Zhang, Yue Yu, Yinghao Li +4
Recent Weak Supervision (WS) approaches have had widespread success in easing the bottleneck of labeling training data for machine learning by synthesizing labels from multiple pot…
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Defu Cao, Yujing Wang, Juanyong Duan +8
Multivariate time-series forecasting plays a crucial role in many real-world applications. It is a challenging problem as one needs to consider both intra-series temporal correlati…
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai +6
Transformer is a ubiquitous model for natural language processing and has attracted wide attentions in computer vision. The attention maps are indispensable for a transformer model…
Deeper Insights into Weight Sharing in Neural Architecture Search
Yuge Zhang, Zejun Lin, Junyang Jiang +5
With the success of deep neural networks, Neural Architecture Search (NAS) as a way of automatic model design has attracted wide attention. As training every child model from scrat…
Customized Graph Embedding: Tailoring Embedding Vectors to different Applications
Bitan Hou, Yujing Wang, Ming Zeng +4
Graph is a natural representation of data for a variety of real-word applications, such as knowledge graph mining, social network analysis and biological network comparison. For th…
DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition
Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang +17
Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing pro…