Search Results for author: Junwei Yang

Found 11 papers, 3 papers with code

Pathway2Text: Dataset and Method for Biomedical Pathway Description Generation

1 code implementation Findings (NAACL) 2022 Junwei Yang, Zequn Liu, Ming Zhang, Sheng Wang

Collectively, we envision our method will become an important benchmark for evaluating Graph2Text methods and advance biomedical research for complex diseases.

named-entity-recognition Named Entity Recognition +2

Unsupervised Adaptive Implicit Neural Representation Learning for Scan-Specific MRI Reconstruction

no code implementations1 Dec 2023 Junwei Yang, Pietro Liò

In recent studies on MRI reconstruction, advances have shown significant promise for further accelerating the MRI acquisition.

MRI Reconstruction Representation Learning

Dual-Domain Multi-Contrast MRI Reconstruction with Synthesis-based Fusion Network

no code implementations1 Dec 2023 Junwei Yang, Pietro Liò

We also compare the reconstruction performance with existing deep learning-based methods using a dataset of brain MRI scans.

MRI Reconstruction

A Comprehensive Survey on Deep Graph Representation Learning

no code implementations11 Apr 2023 Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining.

Graph Embedding Graph Representation Learning

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification

no code implementations21 May 2022 Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang

This problem is typically solved by using graph neural networks (GNNs), which yet rely on a large number of labeled graphs for training and are unable to leverage unlabeled graphs.

Graph Classification

InsCon:Instance Consistency Feature Representation via Self-Supervised Learning

no code implementations15 Mar 2022 Junwei Yang, Ke Zhang, Zhaolin Cui, Jinming Su, Junfeng Luo, Xiaolin Wei

On the other hand, InsCon introduces the pull and push of cell-instance, which utilizes cell consistency to enhance fine-grained feature representation for precise boundary localization.

Contrastive Learning Image Classification +6

Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRI

no code implementations11 Nov 2021 Junwei Yang, Xiao-Xin Li, Feihong Liu, Dong Nie, Pietro Lio, Haikun Qi, Dinggang Shen

Recent studies on T1-assisted MRI reconstruction for under-sampled images of other modalities have demonstrated the potential of further accelerating MRI acquisition of other modalities.

MRI Reconstruction

MIASSR: An Approach for Medical Image Arbitrary Scale Super-Resolution

1 code implementation22 May 2021 Jin Zhu, Chuan Tan, Junwei Yang, Guang Yang, Pietro Lio'

We also employ transfer learning to enable MIASSR to tackle SR tasks of new medical modalities, such as cardiac MR images (ACDC) and chest computed tomography images (COVID-CT).

Image Super-Resolution Meta-Learning +1

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