Search Results for author: Ziqi Gao

Found 9 papers, 3 papers with code

DuDoUniNeXt: Dual-domain unified hybrid model for single and multi-contrast undersampled MRI reconstruction

no code implementations8 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.

MRI Reconstruction

U$^2$MRPD: Unsupervised undersampled MRI reconstruction by prompting a large latent diffusion model

no code implementations16 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.

MRI Reconstruction

GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

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.

Benchmarking Graph Anomaly Detection

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

no code implementations30 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.

Attribute Imputation

MMTSA: Multimodal Temporal Segment Attention Network for Efficient Human Activity Recognition

no code implementations14 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.

Human Activity Recognition

Rethinking Graph Neural Networks for Anomaly Detection

1 code implementation31 May 2022 Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li

Graph Neural Networks (GNNs) are widely applied for graph anomaly detection.

Graph Anomaly Detection

ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification

no code implementations23 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.

Classification Contrastive Learning +2

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