1 code implementation • NeurIPS 2023 • Mengcheng Lan, Xinjiang Wang, Yiping Ke, Jiaxing Xu, Litong Feng, Wayne Zhang
Unsupervised semantic segmentation is a challenging task that segments images into semantic groups without manual annotation.
1 code implementation • 9 Sep 2023 • Qingtian Bian, Jiaxing Xu, Hui Fang, Yiping Ke
To dually improve the performance of temporal states evolution and incremental recommendation, we design a Pseudo-Multi-Task Learning (PMTL) paradigm by stacking the incremental single-target recommendations into one multi-target task for joint optimization.
1 code implementation • 7 Jul 2023 • Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang, Yiping Ke, Miao Qiao, Wei zhang, Wei Khang Jeremy Sim, Balázs Gulyás
Our contributions underscore the potential of ContrastPool for advancing the understanding of brain networks and neurodegenerative conditions.
1 code implementation • 25 May 2023 • Jiaxing Xu, Aihu Zhang, Qingtian Bian, Vijay Prakash Dwivedi, Yiping Ke
We first investigate different kinds of connectivities existing in a local neighborhood and identify a substructure called union subgraph, which is able to capture the complete picture of the 1-hop neighborhood of an edge.
1 code implementation • 20 Mar 2023 • Xinhang Li, Xiangyu Zhao, Jiaxing Xu, Yong Zhang, Chunxiao Xing
To this end, we propose a two-stage multimodal fusion framework to preserve modality-specific knowledge as well as take advantage of the complementarity between different modalities.
1 code implementation • NeurIPS 2023 • Jiaxing Xu, Yunhan Yang, David Tse Jung Huang, Sophi Shilpa Gururajapathy, Yiping Ke, Miao Qiao, Alan Wang, Haribalan Kumar, Josh McGeown, Eryn Kwon
This paper presents a comprehensive and quality collection of functional human brain network data for potential research in the intersection of neuroscience, machine learning, and graph analytics.
no code implementations • 6 Sep 2022 • Jiaxing Xu, Jianbin Cui, Jiangneng Li, Wenge Rong, Noboru Matsuda
One of the main challenges is to collect a sufficient amount of annotated data to train a model.
no code implementations • 2 Sep 2022 • Jiaxing Xu, Jinjie Ni, Sophi Shilpa Gururajapathy, Yiping Ke
In this paper, we propose a Class-Aware Representation rEfinement (CARE) framework for the task of graph classification.