Selected Publications

(2022). Brain Network Transformer. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).

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(2022). On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. Proceedings of the International Conference on Information and Knowledge Management (CIKM).

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(2022). Interpretable GNNs for Connectome-Based Brain Disorder Analysis. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (Oral).

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(2022). Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD).

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(2022). BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks. Under Review.

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(2022). Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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(2022). FBNetGen: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation. Proceedings of the International Conference on Medical Imaging with Deep Learning (MIDL) (Oral).

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(2022). Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning. SIAM International Conference on Data Mining (SDM).

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(2022). How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation. Proceedings of the European Conference on Information Retrieval (ECIR).

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(2021). BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis. International Conference on Machine Learning, Workshop on Interpretable Machine Learning in Healthcare (ICML-IMLH).

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(2021). Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML).

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(2019). Pulmonary Vessel Segmentation based on Orthogonal Fused U-Net++ of Chest CT Images. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI).

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