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Journal Articles
- 2024
[j10]Changlin Wan, Muhan Zhang, Pengtao Dang, Wei Hao, Sha Cao, Pan Li, Chi Zhang:
Ambiguities in neural-network-based hyperedge prediction. J. Appl. Comput. Topol. 8(5): 1333-1361 (2024)- [j9]Zhaogeng Liu
, Feng Ji, Jielong Yang, Xiaofeng Cao, Muhan Zhang, Hechang Chen, Yi Chang:
Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11720-11733 (2024) - 2023
- [j8]Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li:
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 16(11): 2939-2948 (2023) - 2022
- [j7]Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li:
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 15(11): 2788-2796 (2022) - 2021
- [j6]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H. Staib, Pamela Ventola, James S. Duncan:
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Medical Image Anal. 74: 102233 (2021) - 2017
- [j5]Tolutola Oyetunde, Muhan Zhang, Yixin Chen, Yinjie J. Tang, Cynthia Lo:
BoostGAPFILL: improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods. Bioinform. 33(4): 608-611 (2017) - [j4]Wenbin Cai, Muhan Zhang, Ya Zhang:
Batch Mode Active Learning for Regression With Expected Model Change. IEEE Trans. Neural Networks Learn. Syst. 28(7): 1668-1681 (2017) - 2016
- [j3]Lian He, Stephen Gang Wu, Muhan Zhang, Yixin Chen, Yinjie J. Tang:
WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism. BMC Bioinform. 17: 444:1-444:7 (2016) - 2015
- [j2]Wenbin Cai, Muhan Zhang, Ya Zhang:
Active learning for ranking with sample density. Inf. Retr. J. 18(2): 123-144 (2015) - [j1]Wenbin Cai, Muhan Zhang, Ya Zhang:
Active Learning for Web Search Ranking via Noise Injection. ACM Trans. Web 9(1): 3:1-3:31 (2015)
Conference and Workshop Papers
- 2024
- [c45]Xiaojuan Tang, Song-Chun Zhu, Yitao Liang, Muhan Zhang:
RulE: Knowledge Graph Reasoning with Rule Embedding. ACL (Findings) 2024: 4316-4335 - [c44]Jiaqi Li, Mengmeng Wang, Zilong Zheng, Muhan Zhang:
LooGLE: Can Long-Context Language Models Understand Long Contexts? ACL (1) 2024: 16304-16333 - [c43]Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec:
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs. ICLR 2024 - [c42]Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang:
One For All: Towards Training One Graph Model For All Classification Tasks. ICLR 2024 - [c41]Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen:
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability. ICLR 2024 - [c40]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graphs. ICLR 2024 - [c39]Xiyuan Wang, Haotong Yang, Muhan Zhang:
Neural Common Neighbor with Completion for Link Prediction. ICLR 2024 - [c38]Yi Hu, Xiaojuan Tang, Haotong Yang, Muhan Zhang:
Case-Based or Rule-Based: How Do Transformers Do the Math? ICML 2024 - [c37]Xiyuan Wang, Pan Li, Muhan Zhang:
Graph As Point Set. ICML 2024 - [c36]Yanbo Wang, Muhan Zhang:
An Empirical Study of Realized GNN Expressiveness. ICML 2024 - [c35]Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang:
An Efficient Subgraph GNN with Provable Substructure Counting Power. KDD 2024: 3702-3713 - [c34]Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. VLDB Workshops 2024 - [c33]Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang:
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks. WWW 2024: 365-376 - 2023
- [c32]Yifan Chen, Jing Mai, Xiaohan Gao, Muhan Zhang, Yibo Lin:
MacroRank: Ranking Macro Placement Solutions Leveraging Translation Equivariancy. ASP-DAC 2023: 258-263 - [c31]Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang:
CktGNN: Circuit Graph Neural Network for Electronic Design Automation. ICLR 2023 - [c30]Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang:
Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs. ICLR 2023 - [c29]Cai Zhou, Xiyuan Wang, Muhan Zhang:
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks. ICML 2023: 42742-42768 - [c28]Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen:
Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman. NeurIPS 2023 - [c27]Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang:
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network. NeurIPS 2023 - [c26]Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang:
Is Distance Matrix Enough for Geometric Deep Learning? NeurIPS 2023 - [c25]Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang:
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power. NeurIPS 2023 - [c24]Cai Zhou, Xiyuan Wang, Muhan Zhang:
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes. NeurIPS 2023 - 2022
- [c23]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. ICLR 2022 - [c22]Xiyuan Wang, Muhan Zhang:
GLASS: GNN with Labeling Tricks for Subgraph Representation Learning. ICLR 2022 - [c21]Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen:
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs. ICML 2022: 5360-5377 - [c20]Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang:
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design. ICML 2022: 9280-9294 - [c19]Xiyuan Wang, Muhan Zhang:
How Powerful are Spectral Graph Neural Networks. ICML 2022: 23341-23362 - [c18]Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Muhan Zhang, Xueqi Cheng:
Towards Efficient and Expressive GNNs for Graph Classification via Subgraph-Aware Weisfeiler-Lehman. LoG 2022: 17 - [c17]Xiyuan Wang, Muhan Zhang:
Graph Neural Network With Local Frame for Molecular Potential Energy Surface. LoG 2022: 19 - [c16]Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang:
How Powerful are K-hop Message Passing Graph Neural Networks. NeurIPS 2022 - [c15]Lecheng Kong, Yixin Chen, Muhan Zhang:
Geodesic Graph Neural Network for Efficient Graph Representation Learning. NeurIPS 2022 - [c14]Haotong Yang, Zhouchen Lin, Muhan Zhang:
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. NeurIPS 2022 - 2021
- [c13]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. NeurIPS 2021: 9061-9073 - [c12]Muhan Zhang, Pan Li:
Nested Graph Neural Networks. NeurIPS 2021: 15734-15747 - [c11]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS 2021: 19665-19679 - 2020
- [c10]Muhan Zhang, Yixin Chen:
Inductive Matrix Completion Based on Graph Neural Networks. ICLR 2020 - [c9]Muhan Zhang, Christopher Ryan King, Michael Avidan, Yixin Chen:
Hierarchical Attention Propagation for Healthcare Representation Learning. KDD 2020: 249-256 - [c8]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. MICCAI (7) 2020: 625-635 - 2019
- [c7]Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen:
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs. NeurIPS 2019: 1586-1598 - 2018
- [c6]Muhan Zhang, Zhicheng Cui, Shali Jiang, Yixin Chen:
Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space. AAAI 2018: 4430-4437 - [c5]Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen:
An End-to-End Deep Learning Architecture for Graph Classification. AAAI 2018: 4438-4445 - [c4]Zhicheng Cui, Muhan Zhang, Yixin Chen:
Deep Embedding Logistic Regression. ICBK 2018: 176-183 - [c3]Muhan Zhang, Yixin Chen:
Link Prediction Based on Graph Neural Networks. NeurIPS 2018: 5171-5181 - 2017
- [c2]Muhan Zhang, Yixin Chen:
Weisfeiler-Lehman Neural Machine for Link Prediction. KDD 2017: 575-583 - 2015
- [c1]James Gips, Muhan Zhang, Deirdre Anderson:
Towards a Google Glass Based Head Control Communication System for People with Disabilities. HCI (28) 2015: 399-404
Informal and Other Publications
- 2024
- [i66]Cai Zhou, Xiyuan Wang, Muhan Zhang:
Latent Graph Diffusion: A Unified Framework for Generation and Prediction on Graphs. CoRR abs/2402.02518 (2024) - [i65]Zian Li, Xiyuan Wang, Shijia Kang, Muhan Zhang:
On the Completeness of Invariant Geometric Deep Learning Models. CoRR abs/2402.04836 (2024) - [i64]Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li:
Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer. CoRR abs/2402.07268 (2024) - [i63]Yi Hu, Xiaojuan Tang, Haotong Yang, Muhan Zhang:
Case-Based or Rule-Based: How Do Transformers Do the Math? CoRR abs/2402.17709 (2024) - [i62]Fanxu Meng, Zhaohui Wang, Muhan Zhang:
PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models. CoRR abs/2404.02948 (2024) - [i61]Zehao Dong, Muhan Zhang, Yixin Chen:
SPGNN: Recognizing Salient Subgraph Patterns via Enhanced Graph Convolution and Pooling. CoRR abs/2404.13655 (2024) - [i60]Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang:
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs. CoRR abs/2404.18209 (2024) - [i59]Xiyuan Wang, Pan Li, Muhan Zhang:
Graph as Point Set. CoRR abs/2405.02795 (2024) - [i58]Xiaohui Zhang, Yanbo Wang, Xiyuan Wang, Muhan Zhang:
Efficient Neural Common Neighbor for Temporal Graph Link Prediction. CoRR abs/2406.07926 (2024) - [i57]Jiarui Feng, Hao Liu, Lecheng Kong, Yixin Chen, Muhan Zhang:
TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models. CoRR abs/2406.14683 (2024) - [i56]Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen:
Foundations and Frontiers of Graph Learning Theory. CoRR abs/2407.03125 (2024) - [i55]Lecheng Kong, Jiarui Feng, Hao Liu, Chengsong Huang, Jiaxin Huang, Yixin Chen, Muhan Zhang:
GOFA: A Generative One-For-All Model for Joint Graph Language Modeling. CoRR abs/2407.09709 (2024) - [i54]Muhan Zhang:
On Lexical Invariance on Multisets and Graphs. CoRR abs/2409.14179 (2024) - [i53]Junru Zhou, Muhan Zhang:
Fine-Grained Expressive Power of Weisfeiler-Leman: A Homomorphism Counting Perspective. CoRR abs/2410.03517 (2024) - [i52]Zian Li, Cai Zhou, Xiyuan Wang, Xingang Peng, Muhan Zhang:
Geometric Representation Condition Improves Equivariant Molecule Generation. CoRR abs/2410.03655 (2024) - [i51]Xiaojuan Tang, Jiaqi Li, Yitao Liang, Song-Chun Zhu, Muhan Zhang, Zilong Zheng:
Mars: Situated Inductive Reasoning in an Open-World Environment. CoRR abs/2410.08126 (2024) - [i50]Junru Zhou, Cai Zhou, Xiyuan Wang, Pan Li, Muhan Zhang:
Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors. CoRR abs/2410.09737 (2024) - 2023
- [i49]Xiyuan Wang, Haotong Yang, Muhan Zhang:
Neural Common Neighbor with Completion for Link Prediction. CoRR abs/2302.00890 (2023) - [i48]Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang:
Is Distance Matrix Enough for Geometric Deep Learning? CoRR abs/2302.05743 (2023) - [i47]Hao Liu, Muhan Zhang, Zehao Dong, Lecheng Kong, Yixin Chen, Bradley A. Fritz, Dacheng Tao, Christopher Ryan King:
Time Associated Meta Learning for Clinical Prediction. CoRR abs/2303.02570 (2023) - [i46]Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li:
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. CoRR abs/2303.03379 (2023) - [i45]Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang:
Efficiently Counting Substructures by Subgraph GNNs without Running GNN on Subgraphs. CoRR abs/2303.10576 (2023) - [i44]Yanbo Wang, Muhan Zhang:
Towards Better Evaluation of GNN Expressiveness with BREC Dataset. CoRR abs/2304.07702 (2023) - [i43]Xiyuan Wang, Pan Li, Muhan Zhang:
Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks. CoRR abs/2304.10074 (2023) - [i42]Cai Zhou, Xiyuan Wang, Muhan Zhang:
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks. CoRR abs/2305.04963 (2023) - [i41]Xiaojuan Tang, Zilong Zheng, Jiaqi Li, Fanxu Meng, Song-Chun Zhu, Yitao Liang, Muhan Zhang:
Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners. CoRR abs/2305.14825 (2023) - [i40]Yi Hu, Haotong Yang, Zhouchen Lin, Muhan Zhang:
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models. CoRR abs/2305.18507 (2023) - [i39]Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen:
Towards Arbitrarily Expressive GNNs in O(n2) Space by Rethinking Folklore Weisfeiler-Lehman. CoRR abs/2306.03266 (2023) - [i38]Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec:
VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs. CoRR abs/2308.02117 (2023) - [i37]Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang:
CktGNN: Circuit Graph Neural Network for Electronic Design Automation. CoRR abs/2308.16406 (2023) - [i36]Zehao Dong, Muhan Zhang, Qihang Zhao, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Yixin Chen, Fuhai Li:
Universal Normalization Enhanced Graph Representation Learning for Gene Network Prediction. CoRR abs/2309.00738 (2023) - [i35]Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang:
Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power. CoRR abs/2309.04941 (2023) - [i34]Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang:
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks. CoRR abs/2309.10376 (2023) - [i33]Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang:
One for All: Towards Training One Graph Model for All Classification Tasks. CoRR abs/2310.00149 (2023) - [i32]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graph Neural Networks. CoRR abs/2310.02579 (2023) - [i31]Haotong Yang, Fanxu Meng, Zhouchen Lin, Muhan Zhang:
Explaining the Complex Task Reasoning of Large Language Models with Template-Content Structure. CoRR abs/2310.05452 (2023) - [i30]Muhan Zhang:
Neural Attention: Enhancing QKV Calculation in Self-Attention Mechanism with Neural Networks. CoRR abs/2310.11398 (2023) - [i29]Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang:
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network. CoRR abs/2310.19142 (2023) - [i28]Cai Zhou, Xiyuan Wang, Muhan Zhang:
Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes. CoRR abs/2310.19285 (2023) - [i27]Jiaqi Li, Mengmeng Wang, Zilong Zheng, Muhan Zhang:
LooGLE: Can Long-Context Language Models Understand Long Contexts? CoRR abs/2311.04939 (2023) - [i26]Fanxu Meng, Haotong Yang, Yiding Wang, Muhan Zhang:
Chain of Images for Intuitively Reasoning. CoRR abs/2311.09241 (2023) - [i25]Xiyuan Wang, Muhan Zhang:
PyTorch Geometric High Order: A Unified Library for High Order Graph Neural Network. CoRR abs/2311.16670 (2023) - 2022
- [i24]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. CoRR abs/2201.07858 (2022) - [i23]Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li:
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. CoRR abs/2202.13538 (2022) - [i22]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. CoRR abs/2203.00199 (2022) - [i21]Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen:
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs. CoRR abs/2203.10304 (2022) - [i20]Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang:
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design. CoRR abs/2205.07309 (2022) - [i19]Xiyuan Wang, Muhan Zhang:
How Powerful are Spectral Graph Neural Networks. CoRR abs/2205.11172 (2022) - [i18]Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang:
How Powerful are K-hop Message Passing Graph Neural Networks. CoRR abs/2205.13328 (2022) - [i17]Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang:
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR abs/2206.09567 (2022) - [i16]Xiyuan Wang, Muhan Zhang:
Graph Neural Network with Local Frame for Molecular Potential Energy Surface. CoRR abs/2208.00716 (2022) - [i15]Haotong Yang, Zhouchen Lin, Muhan Zhang:
Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. CoRR abs/2209.08858 (2022) - [i14]Lecheng Kong, Yixin Chen, Muhan Zhang:
Geodesic Graph Neural Network for Efficient Graph Representation Learning. CoRR abs/2210.02636 (2022) - [i13]Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang:
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct). CoRR abs/2210.03612 (2022) - [i12]Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang:
Boosting the Cycle Counting Power of Graph Neural Networks with I2-GNNs. CoRR abs/2210.13978 (2022) - [i11]Xiaojuan Tang, Song-Chun Zhu, Yitao Liang, Muhan Zhang:
RulE: Neural-Symbolic Knowledge Graph Reasoning with Rule Embedding. CoRR abs/2210.14905 (2022) - 2021
- [i10]Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang:
Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks. CoRR abs/2106.04292 (2021) - [i9]Muhan Zhang, Pan Li:
Nested Graph Neural Networks. CoRR abs/2110.13197 (2021) - [i8]Xiang Song, Runjie Ma, Jiahang Li, Muhan Zhang, David Paul Wipf:
Network In Graph Neural Network. CoRR abs/2111.11638 (2021) - [i7]Xinshi Chen, Yan Zhu, Haowen Xu, Mengyang Liu, Liang Xiong, Muhan Zhang, Le Song:
Efficient Dynamic Graph Representation Learning at Scale. CoRR abs/2112.07768 (2021) - 2020
- [i6]Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. CoRR abs/2007.14589 (2020) - [i5]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Revisiting Graph Neural Networks for Link Prediction. CoRR abs/2010.16103 (2020) - 2019
- [i4]Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen:
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs. CoRR abs/1904.11088 (2019) - [i3]Muhan Zhang, Yixin Chen:
Inductive Graph Pattern Learning for Recommender Systems Based on a Graph Neural Network. CoRR abs/1904.12058 (2019) - 2018
- [i2]Muhan Zhang, Yixin Chen:
Link Prediction Based on Graph Neural Networks. CoRR abs/1802.09691 (2018) - 2016
- [i1]Muhan Zhang, Zhicheng Cui, Tolutola Oyetunde, Yinjie J. Tang, Yixin Chen:
Recovering Metabolic Networks using A Novel Hyperlink Prediction Method. CoRR abs/1610.06941 (2016)
Coauthor Index
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