3 citations · 4 across the 4 of their papers we have counts for
4 papers
ByteCover3: Accurate Cover Song Identification on Short Queries
Xingjian Du, Zijie Wang, Xia Liang +3
Deep learning based methods have become a paradigm for cover song identification (CSI) in recent years, where the ByteCover systems have achieved state-of-the-art results on all th…
Graph Contrastive Learning with Implicit Augmentations
Huidong Liang, Xingjian Du, Bilei Zhu +3
Existing graph contrastive learning methods rely on augmentation techniques based on random perturbations (e.g., randomly adding or dropping edges and nodes). Nevertheless, alterin…
Wasserstein Adversarially Regularized Graph Autoencoder
Huidong Liang, Junbin Gao
This paper introduces Wasserstein Adversarially Regularized Graph Autoencoder (WARGA), an implicit generative algorithm that directly regularizes the latent distribution of node em…
How Neural Processes Improve Graph Link Prediction
Huidong Liang, Junbin Gao
Link prediction is a fundamental problem in graph data analysis. While most of the literature focuses on transductive link prediction that requires all the graph nodes and majority…