activity
20052022
most citedLearning Backtrackless Aligned-Spatial Graph Convolutional Networks for Graph Classification

90 citations · 222 across the 16 of their papers we have counts for

collaborators

18 papers

cs.CV2022★ 3 cited

Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective

Jiawei Zhang, Xiang Wang, Xiao Bai +7

Despite recent stereo matching networks achieving impressive performance given sufficient training data, they suffer from domain shifts and generalize poorly to unseen domains. We…

cs.CV2020

HMFlow: Hybrid Matching Optical Flow Network for Small and Fast-Moving Objects

Suihanjin Yu, Youmin Zhang, Chen Wang +3

In optical flow estimation task, coarse-to-fine (C2F) warping strategy is widely used to deal with the large displacement problem and provides efficiency and speed. However, limite…

cs.CL2020

Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks

Yue Wang, Zhuo Xu, Lu Bai +5

Joint-event-extraction, which extracts structural information (i.e., entities or triggers of events) from unstructured real-world corpora, has attracted more and more research atte…

cs.SI2020★ 1 cited

A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs

Lu Bai, Lixin Cui, Edwin R. Hancock

In this paper, we develop a new graph kernel, namely the Hierarchical Transitive-Aligned kernel, by transitively aligning the vertices between graphs through a family of hierarchic…

q-fin.ST2019★ 53 cited

Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis

Lu Bai, Lixin Cui, Lixiang Xu +3

In this work, we develop a novel framework to measure the similarity between dynamic financial networks, i.e., time-varying financial networks. Particularly, we explore whether the…

cs.DS2019

A Quantum-inspired Similarity Measure for the Analysis of Complete Weighted Graphs

Lu Bai, Luca Rossi, Lixin Cui +2

We develop a novel method for measuring the similarity between complete weighted graphs, which are probed by means of discrete-time quantum walks. Directly probing complete graphs…