Muhan Zhang

According to our database, Muhan Zhang authored at least 73 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Case-Based or Rule-Based: How Do Transformers Do the Math?

Yi Hu, Xiaojuan Tang, Haotong Yang, Muhan Zhang

CoRR, 2024

Highly Accurate Disease Diagnosis and Highly Reproducible Biomarker Identification with PathFormer.

Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li

CoRR, 2024

On the Completeness of Invariant Geometric Deep Learning Models.

Zian Li, Xiyuan Wang, Shijia Kang, Muhan Zhang

CoRR, 2024

Latent Graph Diffusion: A Unified Framework for Generation and Prediction on Graphs.

Cai Zhou, Xiyuan Wang, Muhan Zhang

CoRR, 2024

2023

SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning.

Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li

Proc. VLDB Endow., 2023

PyTorch Geometric High Order: A Unified Library for High Order Graph Neural Network.

Xiyuan Wang, Muhan Zhang

CoRR, 2023

Chain of Images for Intuitively Reasoning.

Fanxu Meng, Haotong Yang, Yiding Wang, Muhan Zhang

CoRR, 2023

LooGLE: Can Long-Context Language Models Understand Long Contexts?

Jiaqi Li, Mengmeng Wang, Zilong Zheng, Muhan Zhang

CoRR, 2023

MAG-GNN: Reinforcement Learning Boosted Graph Neural Network.

Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang

CoRR, 2023

Neural Attention: Enhancing QKV Calculation in Self-Attention Mechanism with Neural Networks.

Muhan Zhang

CoRR, 2023

Explaining the Complex Task Reasoning of Large Language Models with Template-Content Structure.

Haotong Yang, Fanxu Meng, Zhouchen Lin, Muhan Zhang

CoRR, 2023

On the Stability of Expressive Positional Encodings for Graph Neural Networks.

Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li

CoRR, 2023

One for All: Towards Training One Graph Model for All Classification Tasks.

Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang

CoRR, 2023

Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks.

Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang

CoRR, 2023

Universal Normalization Enhanced Graph Representation Learning for Gene Network Prediction.

Zehao Dong, Muhan Zhang, Qihang Zhao, Philip R. O. Payne, Michael Province, Carlos Cruchaga, Tianyu Zhao, Yixin Chen, Fuhai Li

CoRR, 2023

VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs.

Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec

CoRR, 2023

Towards Arbitrarily Expressive GNNs in O(n²) Space by Rethinking Folklore Weisfeiler-Lehman.

Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen

CoRR, 2023

Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models.

Yi Hu, Haotong Yang, Zhouchen Lin, Muhan Zhang

CoRR, 2023

Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners.

Xiaojuan Tang, Zilong Zheng, Jiaqi Li, Fanxu Meng, Song-Chun Zhu, Yitao Liang, Muhan Zhang

CoRR, 2023

Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks.

Xiyuan Wang, Pan Li, Muhan Zhang

CoRR, 2023

Towards Better Evaluation of GNN Expressiveness with BREC Dataset.

Yanbo Wang, Muhan Zhang

CoRR, 2023

Efficiently Counting Substructures by Subgraph GNNs without Running GNN on Subgraphs.

Zuoyu Yan, Junru Zhou, Liangcai Gao, Zhi Tang, Muhan Zhang

CoRR, 2023

Time Associated Meta Learning for Clinical Prediction.

Hao Liu, Muhan Zhang, Zehao Dong, Lecheng Kong, Yixin Chen, Bradley A. Fritz, Dacheng Tao, Christopher Ryan King

CoRR, 2023

Neural Common Neighbor with Completion for Link Prediction.

Xiyuan Wang, Haotong Yang, Muhan Zhang

CoRR, 2023

Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes.

Cai Zhou, Xiyuan Wang, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power.

Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Is Distance Matrix Enough for Geometric Deep Learning?

Zian Li, Xiyuan Wang, Yinan Huang, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MAG-GNN: Reinforcement Learning Boosted Graph Neural Network.

Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Extending the Design Space of Graph Neural Networks by Rethinking Folklore Weisfeiler-Lehman.

Jiarui Feng, Lecheng Kong, Hao Liu, Dacheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks.

Cai Zhou, Xiyuan Wang, Muhan Zhang

Proceedings of the International Conference on Machine Learning, 2023

Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs.

Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

CktGNN: Circuit Graph Neural Network for Electronic Design Automation.

Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen, Xuan Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MacroRank: Ranking Macro Placement Solutions Leveraging Translation Equivariancy.

Yifan Chen, Jing Mai, Xiaohan Gao, Muhan Zhang, Yibo Lin

Proceedings of the 28th Asia and South Pacific Design Automation Conference, 2023

2022

Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning.

Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li

Proc. VLDB Endow., 2022

RulE: Neural-Symbolic Knowledge Graph Reasoning with Rule Embedding.

Xiaojuan Tang, Song-Chun Zhu, Yitao Liang, Muhan Zhang

CoRR, 2022

Boosting the Cycle Counting Power of Graph Neural Networks with I²-GNNs.

Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

CoRR, 2022

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct).

Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang

CoRR, 2022

Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction.

Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang

CoRR, 2022

Rethinking Knowledge Graph Evaluation Under the Open-World Assumption.

Haotong Yang, Zhouchen Lin, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Geodesic Graph Neural Network for Efficient Graph Representation Learning.

Lecheng Kong, Yixin Chen, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

How Powerful are K-hop Message Passing Graph Neural Networks.

Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph Neural Network With Local Frame for Molecular Potential Energy Surface.

Xiyuan Wang, Muhan Zhang

Proceedings of the Learning on Graphs Conference, 2022

Towards Efficient and Expressive GNNs for Graph Classification via Subgraph-Aware Weisfeiler-Lehman.

Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Muhan Zhang, Xueqi Cheng

Proceedings of the Learning on Graphs Conference, 2022

How Powerful are Spectral Graph Neural Networks.

Xiyuan Wang, Muhan Zhang

Proceedings of the International Conference on Machine Learning, 2022

3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design.

Yinan Huang, Xingang Peng, Jianzhu Ma, Muhan Zhang

Proceedings of the International Conference on Machine Learning, 2022

PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs.

Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen

Proceedings of the International Conference on Machine Learning, 2022

GLASS: GNN with Labeling Tricks for Subgraph Representation Learning.

Xiyuan Wang, Muhan Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks.

Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis.

Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H. Staib, Pamela Ventola, James S. Duncan

Medical Image Anal., 2021

Efficient Dynamic Graph Representation Learning at Scale.

Xinshi Chen, Yan Zhu, Haowen Xu, Mengyang Liu, Liang Xiong, Muhan Zhang, Le Song

CoRR, 2021

Network In Graph Neural Network.

Xiang Song, Runjie Ma, Jiahang Li, Muhan Zhang, David Paul Wipf

CoRR, 2021

Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks.

Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang

CoRR, 2021

Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning.

Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Nested Graph Neural Networks.

Muhan Zhang, Pan Li

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Decoupling the Depth and Scope of Graph Neural Networks.

Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Revisiting Graph Neural Networks for Link Prediction.

Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin

CoRR, 2020

Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis.

Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Hierarchical Attention Propagation for Healthcare Representation Learning.

Muhan Zhang, Christopher Ryan King, Michael Avidan, Yixin Chen

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Inductive Matrix Completion Based on Graph Neural Networks.

Muhan Zhang, Yixin Chen

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Inductive Graph Pattern Learning for Recommender Systems Based on a Graph Neural Network.

Muhan Zhang, Yixin Chen

CoRR, 2019

D-VAE: A Variational Autoencoder for Directed Acyclic Graphs.

Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Link Prediction Based on Graph Neural Networks.

Muhan Zhang, Yixin Chen

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Embedding Logistic Regression.

Zhicheng Cui, Muhan Zhang, Yixin Chen

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

An End-to-End Deep Learning Architecture for Graph Classification.

Muhan Zhang, Zhicheng Cui, Marion Neumann, Yixin Chen

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space.

Muhan Zhang, Zhicheng Cui, Shali Jiang, Yixin Chen

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Batch Mode Active Learning for Regression With Expected Model Change.

Wenbin Cai, Muhan Zhang, Ya Zhang

IEEE Trans. Neural Networks Learn. Syst., 2017

BoostGAPFILL: improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods.

Tolutola Oyetunde, Muhan Zhang, Yixin Chen, Yinjie J. Tang, Cynthia Lo

Bioinform., 2017

Weisfeiler-Lehman Neural Machine for Link Prediction.

Muhan Zhang, Yixin Chen

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

Recovering Metabolic Networks using A Novel Hyperlink Prediction Method.

Muhan Zhang, Zhicheng Cui, Tolutola Oyetunde, Yinjie J. Tang, Yixin Chen

CoRR, 2016

WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism.

Lian He, Stephen Gang Wu, Muhan Zhang, Yixin Chen, Yinjie J. Tang

BMC Bioinform., 2016

2015

Active Learning for Web Search Ranking via Noise Injection.

Wenbin Cai, Muhan Zhang, Ya Zhang

ACM Trans. Web, 2015

Active learning for ranking with sample density.

Wenbin Cai, Muhan Zhang, Ya Zhang

Inf. Retr. J., 2015

Towards a Google Glass Based Head Control Communication System for People with Disabilities.

James Gips, Muhan Zhang, Deirdre Anderson

Proceedings of the HCI International 2015 - Posters' Extended Abstracts, 2015