Search Results for author: Alexander Zhou

Found 7 papers, 1 papers with code

Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements

no code implementations1 Jan 2025 Haoyang Li, Yuming Xu, Chen Jason Zhang, Alexander Zhou, Lei Chen, Qing Li

Graph-level tasks, which predict properties or classes for the entire graph, are critical for applications, such as molecular property prediction and subgraph counting.

Contrastive Learning Graph Classification +3

Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting

no code implementations26 Nov 2024 Yufan Zheng, Wei Jiang, Alexander Zhou, Nguyen Quoc Viet Hung, Choujun Zhan, Tong Chen

With the time-varying mechanistic affinity graphs computed with the epidemiology-informed location embeddings, a heterogeneous transmission graph network is designed to encode the mechanistic heterogeneity among locations, providing additional predictive signals to facilitate accurate forecasting.

Epidemiology Graph Neural Network

VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification

1 code implementation1 Feb 2024 Zelong Liu, Andrew Tieu, Nikhil Patel, Georgios Soultanidis, Louisa Deyer, Ying Wang, Sean Huver, Alexander Zhou, Yunhao Mei, Zahi A. Fayad, Timothy Deyer, Xueyan Mei

VIS-MAE represents a significant advancement in medical imaging AI, offering a generalizable and robust solution for improving segmentation and classification tasks while reducing the data annotation workload.

Image Segmentation Medical Image Segmentation +3

RadImageGAN -- A Multi-modal Dataset-Scale Generative AI for Medical Imaging

no code implementations10 Dec 2023 Zelong Liu, Alexander Zhou, Arnold Yang, Alara Yilmaz, Maxwell Yoo, Mikey Sullivan, Catherine Zhang, James Grant, Daiqing Li, Zahi A. Fayad, Sean Huver, Timothy Deyer, Xueyan Mei

We showed that using synthetic auto-labeled data from RadImageGAN can significantly improve performance on four diverse downstream segmentation datasets by augmenting real training data and/or developing pre-trained weights for fine-tuning.

Segmentation

Fast-adapting and Privacy-preserving Federated Recommender System

no code implementations2 Apr 2021 Qinyong Wang, Hongzhi Yin, Tong Chen, Junliang Yu, Alexander Zhou, Xiangliang Zhang

In the mobile Internet era, the recommender system has become an irreplaceable tool to help users discover useful items, and thus alleviating the information overload problem.

Federated Learning Meta-Learning +2

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