Tengfei Ma

Full list: Google Scholar   

Graph Learning

1. Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu. IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research. In KDD 2023 Applied Data Science (ADS) track.
2. Tengfei Ma, Trong Nghia Hoang, Jie Chen. Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs. In The 39th Conference on Uncertainty in Artificial Intelligence (UAI), 2023.
3. EunJeong Hwang, Veronika Thost, Shib Sankar Dasgupta, Tengfei Ma. An Analysis of Virtual Nodes in Graph Neural Networks for Link Prediction (Extended Abstract). In The First Learning on Graphs Conference (LoG), 2022. (Spotlight)
4. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen. Neural Approximation of Extended Persistent Homology on Graphs. In Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
5. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen. Cycle Representation Learning for Inductive Relation Prediction. In The 39th International Conference on Machine Learning (ICML), 2022.
6. Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp and Jens Lehmann. Improving Inductive Link Prediction Using Hyper-Relational Facts. In The 20th International Semantic Web Conference (ISWC), 2021. (Best Paper Award - Research Track)
7. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen. Persistence Homology for Link Prediction: An Interactive View. In The Thirty-eighth International Conference on Machine Learning (ICML), 2021.
8. Tengfei Ma*, Jie Chen*. Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. In the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021. (*equal contribution.)
9. Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen. Curvature Graph Network. In the Eighth International Conference on Learning Representations (ICLR), 2020.
10. Aldo Pareja*, Giacomo Domeniconi*, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leisersen. EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. In the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
11. Junyuan Shang, Tengfei Ma, Cao Xiao, and Jimeng Sun. Pre-training of Graph Augmented Transformers for Medication Recommendation. In the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019.
12. Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun. GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination. In the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.
13. Tengfei Ma*, Jie Chen*, Cao Xiao. Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. In Neural Information Processing Systems (NeurIPS), 2018. (*Equal contribution.)
14. Tengfei Ma, Cao Xiao, Jiayu Zhou, Fei Wang. Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders. In the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI), 2018.
15. Jie Chen*, Tengfei Ma*, Cao Xiao. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In the Sixth International Conference on Learning Representations (ICLR), 2018. (*Equal contribution.)

Biomedical, NLP and others

16. Nate T. Garland*, Joseph W. Song*, Tengfei Ma*, Yong Jae Kim*, Abraham Vázquez-Guardado, Ayemeh Bagheri Hashkavayi, Sankalp Koduvayur Ganeshan, Nivesh Sharma, Hanjun Ryu, Min-Kyu Lee, Brandon Sumpio, Margaret A. Jakus, Viviane Forsberg, Rajaram Kaveti, Samuel K. Sia, Aristidis Veves, John A. Rogers, Guillermo A. Ameer, Amay J. Bandodkar. A Miniaturized, Battery-free, Wireless Wound Monitor that Predicts Wound Closure Rate Early. In Advanced Healthcare Materials, 2023. (* equal contribution)
17. Ruixuan Yan, Yunshi Wen, Debarun Bhattacharjya, Ronny Luss, Tengfei Ma, Achille Fokoue, Anak Agung Julius. Weighted Clock Logic Point Process. In The Eleventh International Conference on Learning Representations (ICLR), 2023.
18. Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji and Kathleen McKeown. Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport. In The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.
19. Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Bo Long and Shouling Ji. Constructing Contrastive Samples via Summarization for Text Classification with Limited Annotations. In The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP) Findings, 2021
20. Hanlu Wu*, Tengfei Ma*, Lingfei Wu, Tariro Manyumwa, Shouling Ji. Unsupervised Reference- Free Summary Quality Evaluation via Contrastive Learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020. (*equal contribution.)
21. Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen and Michael Katz. Adaptive Planner Scheduling with Graph Neural Networks. In the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
22. Cao Xiao*, Tengfei Ma*, Adji B. Dieng, David Blei, Fei Wang. Readmission Prediction via Deep Contextual Embedding of Clinical Concepts. (*Equal contribution). In PLOS ONE, 2018.
23. Tengfei Ma*, Cao Xiao*, Fei Wang. Health-ATM: A Deep Architecture for Multifaceted Patient Health Record Representation and Risk Prediction. In SIAM International Conference on Data Mining (SDM), 2018. (*Equal contribution)
24. Tengfei Ma, Tetsuya Nasukawa. Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel Data. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 2017.
25. Long Duong, Hiroshi Kanayama, Tengfei Ma, Steven Bird, Trevor Cohn. Learning Crosslingual Word Embeddings without Bilingual Corpora. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP), Austin, Texas, USA, pp. 1285– 1295, 2016.