---
title: "Rex Ying — all works — Elamur Research"
description: "All 32 works of Rex Ying in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/rex-ying/works/"
---
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# Rex Ying — all works

32 works · [← Rex Ying](https://md.research.elamur.ai/free/en/authors/rex-ying/)

1. [**Inductive Representation Learning on Large Graphs arXiv:1706.02216**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,795 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/)
2. **[Graph Convolutional Neural Networks for Web-Scale Recommender Systems ↗](https://doi.org/10.1145/3219819.3219890) ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) · no summary yet**Rex Ying et al.*2018 · 3,023 citations*
3. **[Hierarchical graph representation learning with differentiable pooling ↗](https://openalex.org/W2811124557) neural information processing systems · no summary yet**Zhitao Ying et al.*2018 · 865 citations*
4. **[GNNExplainer: Generating Explanations for Graph Neural Networks ↗](https://arxiv.org/abs/1903.03894) arXiv (Cornell University) · no summary yet**Rex Ying et al.*2019 · 685 citations*
5. **[GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models ↗](https://arxiv.org/abs/1802.08773) arXiv (Cornell University) · no summary yet**Jiaxuan You et al.*2018 · 490 citations*
6. **[Learning to Simulate Complex Physics with Graph Networks ↗](https://arxiv.org/abs/2002.09405) arXiv:2002.09405 · no summary yet**Alvaro Sanchez-Gonzalez et al.*2020 · 462 citations*
7. **[Representation Learning on Graphs: Methods and Applications ↗](https://arxiv.org/abs/1709.05584) arXiv (Cornell University) · no summary yet**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 366 citations*
8. **[Hyperbolic Graph Convolutional Neural Networks ↗](https://arxiv.org/abs/1910.12933) arXiv (Cornell University) · no summary yet**Ines Chami et al.*2019 · 291 citations*
9. **[Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation ↗](https://arxiv.org/abs/1806.02473) arXiv (Cornell University) · no summary yet**Jiaxuan You et al.*2018 · 259 citations*
10. **[Design Space for Graph Neural Networks ↗](https://arxiv.org/abs/2011.08843) arXiv (Cornell University) · no summary yet**Jiaxuan You, Rex Ying, Jure Leskovec*2020 · 176 citations*
11. **[Identity-aware Graph Neural Networks ↗](https://doi.org/10.1609/aaai.v35i12.17283) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Jiaxuan You et al.*2021 · 159 citations*
12. **[Multi-hop Attention Graph Neural Networks ↗](https://doi.org/10.24963/ijcai.2021/425) no summary yet**Guangtao Wang et al.*2021 · 111 citations*
13. **[Position-aware Graph Neural Networks ↗](https://arxiv.org/abs/1906.04817) arXiv (Cornell University) · no summary yet**Jiaxuan You, Rex Ying, Jure Leskovec*2019 · 94 citations*
14. **[Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification ↗](https://aclanthology.org/2021.naacl-main.229/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Xiaochen Hou et al.*2021 · 62 citations*
15. **[From Similarity to Superiority: Channel Clustering for Time Series Forecasting ↗](https://doi.org/10.52202/079017-4152) neural information processing systems · no summary yet**Jialin Chen et al.*2024 · 44 citations*
16. **[Bipartite Dynamic Representations for Abuse Detection ↗](https://doi.org/10.1145/3447548.3467141) no summary yet**Andrew Z. Wang et al.*2021 · 35 citations*
17. **[Multi-hop Attention Graph Neural Network ↗](https://arxiv.org/abs/2009.14332) arXiv (Cornell University) · no summary yet**Guangtao Wang et al.*2020 · 34 citations*
18. **[Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator ↗](https://doi.org/10.1145/3534678.3539045) ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · no summary yet**Tailin Wu et al.*2022 · 33 citations*
19. **[Improving Graph Attention Networks with Large Margin-based Constraints ↗](https://arxiv.org/abs/1910.11945) arXiv (Cornell University) · no summary yet**Guangtao Wang et al.*2019 · 25 citations*
20. **[Relational Deep Learning: Graph Representation Learning on Relational Databases ↗](https://arxiv.org/abs/2312.04615) arXiv (Cornell University) · no summary yet**Matthias Fey et al.*2023 · 23 citations*
21. **[Direct Multi-hop Attention based Graph Neural Network ↗](http://dblp.uni-trier.de/db/journals/corr/corr2009.html#abs-2009-14332) arXiv (Cornell University) · no summary yet**Guangtao Wang et al.*2020 · 20 citations*
22. **[Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones ↗](https://arxiv.org/abs/2110.14923) arXiv (Cornell University) · no summary yet**Yushi Bai et al.*2021 · 18 citations*
23. **[MUDiff: Unified Diffusion for Complete Molecule Generation ↗](https://arxiv.org/abs/2304.14621) arXiv (Cornell University) · no summary yet**Chenqing Hua et al.*2023 · 14 citations*
24. **[Neural Distance Embeddings for Biological Sequences ↗](https://doi.org/10.17863/cam.78685) arXiv (Cornell University) · no summary yet**Gabriele Corso et al.*2021 · 12 citations*
25. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
26. **[Redundancy-Free Computation Graphs for Graph Neural Networks ↗](https://arxiv.org/abs/1906.03707) arXiv (Cornell University) · no summary yet**Zhihao Jia et al.*2019 · 9 citations*
27. **[Experience Retrieval-Augmentation with Electronic Health Records Enables Accurate Discharge QA](https://md.research.elamur.ai/free/en/papers/ou-2026-experience-retrieval-augmentation-electronic-health/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Justice Ou, Tinglin Huang, Yilun Zhao, et al.*2026 · 4 citations*
28. **[Representation Learning for Frequent Subgraph Mining ↗](https://arxiv.org/abs/2402.14367) arXiv (Cornell University) · no summary yet**Rex Ying et al.*2024 · 4 citations*
29. **[Learning Graph Search Heuristics ↗](https://arxiv.org/abs/2212.03978) arXiv (Cornell University) · no summary yet**Michal Pándy et al.*2022 · 2 citations*
30. **[Efficient Automatic Machine Learning via Design Graphs ↗](https://arxiv.org/abs/2210.12257) arXiv (Cornell University) · no summary yet**Wu, Shirley et al.*2022 · 1 citation*
31. **[OTel: Open Telco AI Datasets, Benchmarks, and Models ↗](https://arxiv.org/abs/2610.07766) arXiv (Cornell University) · no summary yet**Farbod Tavakkoli et al.*2026*
32. **[Accelerating predictive modeling of laser-driven ion acceleration with deep learning ↗](https://openalex.org/W3206333248) Bulletin of the American Physical Society · no summary yet**Jason Chou et al.*2021*