no code implementations • 8 Mar 2024 • Ziqi Gao, Yue Zhang, Xinwen Liu, Kaiyan Li, S. Kevin Zhou
Multi-contrast (MC) Magnetic Resonance Imaging (MRI) reconstruction aims to incorporate a reference image of auxiliary modality to guide the reconstruction process of the target modality.
no code implementations • 16 Feb 2024 • Ziqi Gao, S. Kevin Zhou
To the best of our knowledge, U$^2$MRPD is the {\bf first} unsupervised method that demonstrates the universal prowess of a LLDM, %trained on magnitude-only natural images in medical imaging, attaining the best adaptability for both MRI database-free and database-available scenarios and generalizability towards out-of-domain data.
1 code implementation • NeurIPS 2023 • Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li
With a long history of traditional Graph Anomaly Detection (GAD) algorithms and recently popular Graph Neural Networks (GNNs), it is still not clear (1) how they perform under a standard comprehensive setting, (2) whether GNNs can outperform traditional algorithms such as tree ensembles, and (3) how about their efficiency on large-scale graphs.
no code implementations • 19 Mar 2023 • Ziqi Gao, S. Kevin Zhou
Undersampled MRI reconstruction is crucial for accelerating clinical scanning.
no code implementations • 30 Nov 2022 • Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li
In this work, we present a regularized graph autoencoder for graph attribute imputation, named MEGAE, which aims at mitigating spectral concentration problem by maximizing the graph spectral entropy.
no code implementations • 14 Oct 2022 • Ziqi Gao, Yuntao Wang, Jianguo Chen, Junliang Xing, Shwetak Patel, Xin Liu, Yuanchun Shi
The efficiency evaluation on an edge device showed that MMTSA achieved significantly better accuracy, lower computational load, and lower inference latency than SOTA methods.
1 code implementation • 16 Sep 2022 • Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Yang Yu, Chan Lu, Zhipeng Zhou, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng
The last decade has witnessed a prosperous development of computational methods and dataset curation for AI-aided drug discovery (AIDD).
1 code implementation • 31 May 2022 • Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li
Graph Neural Networks (GNNs) are widely applied for graph anomaly detection.
no code implementations • 23 May 2022 • Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li
Motivated by this observation, we propose a principled GCL framework on Imbalanced node classification (ImGCL), which automatically and adaptively balances the representations learned from GCL without labels.