🧑‍🔬 Rex Ying

🏛️ Affiliations

🎓Yale UniversityNew Haven · United States2022–2026 · 101 paperscurrent🎓Stanford UniversityStanford · United States2015–2022 · 28 papers🎓Pennsylvania State UniversityState College · United States2021–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Inductive Representation Learning on Large Graphs (2017 · 4,795 citations)
   Most earlier node-embedding techniques, such as factorization or random-walk objectives, fit a separate vector for every node of one fixed graph.
2. Implicit Reasoning in Large Language Models: A Comprehensive Survey (2025 · 10 citations)
   Chain-of-Thought prompting makes LLMs write out every intermediate step, which inflates output length, latency and cost.
3. Experience Retrieval-Augmentation with Electronic Health Records Enables Accurate Discharge QA (2026 · 4 citations)
   LLMs used for clinical question answering often hallucinate. Standard RAG mostly supplies generic medical facts, such as a drug's usual dose, which ignore the combination of conditions a real patient has. The authors argue that models, like experienced clinicians, benefit from looking at comparable past cases. They…

All works

32 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Inductive Representation Learning on Large GraphsarXiv:1706.02216William L. Hamilton, Rex Ying, Jure Leskovec2017 · 4,795 citations
2. Graph Convolutional Neural Networks for Web-Scale Recommender Systems ↗ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) · no summary yetRex Ying et al.2018 · 3,023 citations
3. Hierarchical graph representation learning with differentiable pooling ↗neural information processing systems · no summary yetZhitao Ying et al.2018 · 865 citations
4. GNNExplainer: Generating Explanations for Graph Neural Networks ↗arXiv (Cornell University) · no summary yetRex Ying et al.2019 · 685 citations
5. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models ↗arXiv (Cornell University) · no summary yetJiaxuan You et al.2018 · 490 citations
6. Learning to Simulate Complex Physics with Graph Networks ↗arXiv:2002.09405 · no summary yetAlvaro Sanchez-Gonzalez et al.2020 · 462 citations
7. Representation Learning on Graphs: Methods and Applications ↗arXiv (Cornell University) · no summary yetWilliam L. Hamilton, Rex Ying, Jure Leskovec2017 · 366 citations
8. Hyperbolic Graph Convolutional Neural Networks ↗arXiv (Cornell University) · no summary yetInes Chami et al.2019 · 291 citations
9. Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation ↗arXiv (Cornell University) · no summary yetJiaxuan You et al.2018 · 259 citations
10. Design Space for Graph Neural Networks ↗arXiv (Cornell University) · no summary yetJiaxuan You, Rex Ying, Jure Leskovec2020 · 176 citations
11. Identity-aware Graph Neural Networks ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetJiaxuan You et al.2021 · 159 citations
12. Multi-hop Attention Graph Neural Networks ↗no summary yetGuangtao Wang et al.2021 · 111 citations
13. Position-aware Graph Neural Networks ↗arXiv (Cornell University) · no summary yetJiaxuan You, Rex Ying, Jure Leskovec2019 · 94 citations
14. Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetXiaochen Hou et al.2021 · 62 citations
15. From Similarity to Superiority: Channel Clustering for Time Series Forecasting ↗neural information processing systems · no summary yetJialin Chen et al.2024 · 44 citations
16. Bipartite Dynamic Representations for Abuse Detection ↗no summary yetAndrew Z. Wang et al.2021 · 35 citations
17. Multi-hop Attention Graph Neural Network ↗arXiv (Cornell University) · no summary yetGuangtao Wang et al.2020 · 34 citations
18. Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator ↗ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetTailin Wu et al.2022 · 33 citations
19. Improving Graph Attention Networks with Large Margin-based Constraints ↗arXiv (Cornell University) · no summary yetGuangtao Wang et al.2019 · 25 citations
20. Relational Deep Learning: Graph Representation Learning on Relational Databases ↗arXiv (Cornell University) · no summary yetMatthias Fey et al.2023 · 23 citations
21. Direct Multi-hop Attention based Graph Neural Network ↗arXiv (Cornell University) · no summary yetGuangtao Wang et al.2020 · 20 citations
22. Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones ↗arXiv (Cornell University) · no summary yetYushi Bai et al.2021 · 18 citations
23. MUDiff: Unified Diffusion for Complete Molecule Generation ↗arXiv (Cornell University) · no summary yetChenqing Hua et al.2023 · 14 citations
24. Neural Distance Embeddings for Biological Sequences ↗arXiv (Cornell University) · no summary yetGabriele Corso et al.2021 · 12 citations
25. Implicit Reasoning in Large Language Models: A Comprehensive SurveyarXiv:2509.02350Jindong Li, Yali Fu, Li Fan, et al.2025 · 10 citations

See all 32 works by Rex Ying →

🤝 Co-authors here

12 co-authors with a page, the most papers together first.

• Chengwei Qin
• Irwin King
• Jiahong Liu
• Jindong Li
• Jure Leskovec
• Justice Ou
• Menglin Yang
• Tinglin Huang
• William L. Hamilton
• Yao Shu
• Yifei Shen
• Yilun Zhao

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• neural information processing systems ×2
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
• ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD)
• Bulletin of the American Physical Society
• Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
• Proceedings of the AAAI Conference on Artificial Intelligence

🔗 Cited by

Papers of our library cite their works 1,650 times (of the 149,439 papers whose bibliographies we read); 139 citing papers with a page here →.

Updated 1 November 2026

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