Pan Li

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Suautori

Olgica MilenkovicUniversity of IllinoisPotvrđena adresa e-pošte na illinois.edu
Eli ChienGeorgia Institute of TechnologyPotvrđena adresa e-pošte na gatech.edu
Muhan ZhangPeking UniversityPotvrđena adresa e-pošte na pku.edu.cn
Jure LeskovecProfessor of Computer Science, Stanford UniversityPotvrđena adresa e-pošte na cs.stanford.edu
Carl J. YangAssistant Professor of Computer Science at Emory UniversityPotvrđena adresa e-pošte na emory.edu
Mia LiuPurdue UniversityPotvrđena adresa e-pošte na purdue.edu
Cong (Callie) HaoGeorgia Institute of TechnologyPotvrđena adresa e-pošte na gatech.edu
Jennifer NevilleMicrosoft Research, Purdue UniversityPotvrđena adresa e-pošte na microsoft.com
Jianzhu MaTsinghua UniversityPotvrđena adresa e-pošte na tsinghua.edu.cn
Zhangyang (Atlas) WangXTX Markets & University of Texas at AustinPotvrđena adresa e-pošte na utexas.edu
Tailin WuAssistant professor at Westlake University; previously postdoc@Stanford CS, PhD at MITPotvrđena adresa e-pošte na cs.stanford.edu
Deming ChenAbel Bliss Professor. University of Illinois at Urbana-ChampaignPotvrđena adresa e-pošte na illinois.edu
Han ZhaoDepartment of Computer Science, University of Illinois Urbana-ChampaignPotvrđena adresa e-pošte na illinois.edu
Niao HeAssociate Professor, ETH ZürichPotvrđena adresa e-pošte na inf.ethz.ch
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisPotvrđena adresa e-pošte na cs.uiuc.edu
David GleichPurdue UniversityPotvrđena adresa e-pošte na purdue.edu
Nate VeldtTexas A&M UniversityPotvrđena adresa e-pošte na tamu.edu
Stefanie JegelkaTUM and MITPotvrđena adresa e-pošte na mit.edu
Arya MazumdarUniversity of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu

Prati

Pan Li

Georgia Institute of Technology, Purdue University

Potvrđena adresa e-pošte na gatech.edu - Početna stranica

Machine learning on Graphs Algorithm Optimization Network Science


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Adaptive universal generalized pagerank graph neural network E Chien, J Peng, P Li, O Milenkovic International Conference on Learning Representations, 2021	882	2021
Distance encoding: Design provably more powerful neural networks for graph representation learning P Li, Y Wang, H Wang, J Leskovec Advances in Neural Information Processing Systems 33, 4465-4478, 2020	401	2020
Adversarial graph augmentation to improve graph contrastive learning S Suresh, P Li, C Hao, J Neville Advances in Neural Information Processing Systems 34, 15920-15933, 2021	380	2021
Inductive representation learning in temporal networks via causal anonymous walks Y Wang, YY Chang, Y Liu, J Leskovec, P Li International Conference on Learning Representations, 2021	302	2021
Labeling trick: A theory of using graph neural networks for multi-node representation learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems 34, 9061-9073, 2021	292*	2021
Graph information bottleneck T Wu, H Ren, P Li, J Leskovec Advances in Neural Information Processing Systems 33, 20437-20448, 2020	284	2020
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism S Miao, M Liu, P Li International Conference on Machine Learning, 15524-15543, 2022	235	2022
Inhomogeneous hypergraph clustering with applications P Li, O Milenkovic Advances in Neural Information Processing Systems, 2017	187	2017
Nested Graph Neural Networks M Zhang, P Li Advances in Neural Information Processing Systems, 2021	183	2021
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns S Suresh, V Budde, J Neville, P Li, J Ma Proceedings of the ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021	149	2021
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks H Wang, H Yin, M Zhang, P Li International Conference on Learning Representations, 2022	139	2022
Submodular hypergraphs: p-laplacians, cheeger inequalities and spectral clustering P Li, O Milenkovic International Conference on Machine Learning, 3014-3023, 2018	122	2018
Conditional structure generation through graph variational generative adversarial nets C Yang, P Zhuang, W Shi, A Luu, P Li Advances in Neural Information Processing Systems, 2019	112	2019
On positional and structural node features for graph neural networks on non-attributed graphs H Cui, Z Lu, P Li, C Yang Proceedings of the 31st ACM International Conference on Information …, 2022	97	2022
Motif and hypergraph correlation clustering P Li, GJ Puleo, O Milenkovic IEEE Transactions on Information Theory 66 (5), 3065-3078, 2019	97*	2019
Better trigger inversion optimization in backdoor scanning G Tao, G Shen, Y Liu, S An, Q Xu, S Ma, P Li, X Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	87	2022
Optimizing generalized pagerank methods for seed-expansion community detection P Li, E Chien, O Milenkovic Advances in Neural Information Processing Systems, 2019	80	2019
Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction M Tang, C Yang, P Li International Conference on Learning Representations, 2022	70	2022
MSTREAM: Fast anomaly detection in multi-aspect streams S Bhatia, A Jain, P Li, R Kumar, B Hooi Proceedings of the Web Conference, 2021	69	2021
Applications and techniques for fast machine learning in science AMC Deiana, N Tran, J Agar, M Blott, G Di Guglielmo, J Duarte, P Harris, ... Frontiers in big Data 5, 2022	67	2022

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