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Graph Neural Network (GNN) research is rapidly growing thanks to the capacity of GNNs in learning distributed representations from graph-structured data.
Chaoyang He, Tian Xie, Yu Rong, W. Huang, Junzhou Huang, X. Ren, and C. Shahabi · 1906
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Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, and Cyrus Shahabi · 1906
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Central server free federated learning over single-sided trust social networks
Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, and Ji Liu · 1910
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Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. correlation with molecular orbital energies and hydrophobicity
Asim Kumar Debnath, Rosa L Lopez de Compadre, Gargi Debnath, Alan J Shusterman, and Corwin Hansch · 1991
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The properties of known drugs. 1. molecular frameworks
Guy W Bemis and Mark A Murcko · 1996
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Citeseer: An automatic citation indexing system
C. Lee Giles, Kurt D. Bollacker, and Steve Lawrence · 1998
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Automating the construction of internet portals with machine learning
Andrew Kachites McCallum, Kamal Nigam, Jason Rennie, and Kristie Seymore · 2000
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Evaluating web-based question answering systems
Dragomir R Radev, Hong Qi, Harris Wu, and Weiguo Fan · 2002
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Trust management for the semantic web
Matthew Richardson, Rakesh Agrawal, and Pedro Domingos · 2003
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Esol: estimating aqueous solubility directly from molecular structure
John S Delaney · 2004
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Fednas: Federated deep learning via neural architecture search
Chaoyang He, Murali Annavaram, and Salman Avestimehr · 2004
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Protein function prediction via graph kernels
Karsten M Borgwardt, Cheng Soon Ong, Stefan Schönauer, SVN Vishwanathan, Alex J Smola, and Hans-Peter Kriegel · 2005
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Rdkit: Open-source cheminformatics, 2006
Greg Landrum · 2006
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Fedml: A research library and benchmark for federated machine learning
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, and Salman Avestimehr · 2007
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Exploring network structure, dynamics, and function using networkx
Aric A. Hagberg, Daniel A. Schult, and Pieter J. Swart · 2008
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Iam graph database repository for graph based pattern recognition and machine learning
Kaspar Riesen and Horst Bunke · 2008
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Collective classification in network data
Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad · 2008
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Arnetminer: extraction and mining of academic social networks
Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su · 2008
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Comparison of descriptor spaces for chemical compound retrieval and classification
Nikil Wale, Ian A Watson, and George Karypis · 2008
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Wireless sensor network survey
Jennifer Yick, Biswanath Mukherjee, and Dipak Ghosal · 2008
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A brief survey on anonymization techniques for privacy preserving publishing of social network data
Bin Zhou, Jian Pei, and WoShun Luk · 2008
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Maximum unbiased validation (muv) data sets for virtual screening based on pubchem bioactivity data
Sebastian G Rohrer and Knut Baumann · 2009
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Distdgl: Distributed graph neural network training for billion-scale graphs
Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, and George Karypis · 2010
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Asfgnn: Automated separated-federated graph neural network
Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, and Benyu Zhang · 2011
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Chembl: a large-scale bioactivity database for drug discovery
Anna Gaulton, Louisa J Bellis, A Patricia Bento, Jon Chambers, Mark Davies, Anne Hersey, Yvonne Light, Shaun McGlinchey, David Michalovich, Bissan Al-Lazikani, et al · 2012
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A bayesian approach to in silico blood-brain barrier penetration modeling
Ines Filipa Martins, Ana L Teixeira, Luis Pinheiro, and Andre O Falcao · 2012
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mtrust: Discerning multi-faceted trust in a connected world
Jiliang Tang, Huiji Gao, and Huan Liu · 2012
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Graphfl: A federated learning framework for semi-supervised node classification on graphs
Binghui Wang, Ang Li, Hai Li, and Yiran Chen · 2012
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Yago3: A knowledge base from multilingual wikipedias
Farzaneh Mahdisoltani, Joanna Biega, and Fabian M. Suchanek · 2013
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Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
Isabel Segura Bedmar, Paloma Martínez, and María Herrero Zazo · 2013
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Freesolv: a database of experimental and calculated hydration free energies, with input files
David L Mobley and J Peter Guthrie · 2014
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Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O Dral, Matthias Rupp, and O Anatole von Lilienfeld · 2014
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
Advances and open problems in federated learning
Peter Kairouz, H Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al · 2019
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Pitfalls of graph neural network evaluation, 2019
Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, and Stephan Günnemann · 2019
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Graph convolutional networks for computational drug development and discovery
Mengying Sun, Sendong Zhao, Coryandar Gilvary, Olivier Elemento, Jiayu Zhou, and Fei Wang · 2019
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Simplifying graph convolutional networks, 2019
Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr. au2, Christopher Fifty, Tao Yu, and Kilian Q. Weinberger · 2019
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How powerful are graph neural networks?, 2019
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019
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Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen · 2015
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Deep Graph Kernels , pp. 1365–1374
Pinar Yanardag and S.V.N. Vishwanathan · 2015
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The ChEMBL database in 2017
Anna Gaulton, Anne Hersey, Michał Nowotka, A. Patrícia Bento, Jon Chambers, David Mendez, Prudence Mutowo, Francis Atkinson, Louisa J. Bellis, Elena Cibrián-Uhalte, Mark Davies, Nathan Dedman, Anneli Karlsson, María Paula Magariños, John P. Overington, George Papadatos, Ines Smit, and Andrew R. Leach · 2016
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A data-driven approach to predicting successes and failures of clinical trials
Kaitlyn M Gayvert, Neel S Madhukar, and Olivier Elemento · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
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The sider database of drugs and side effects
Michael Kuhn, Ivica Letunic, Lars Juhl Jensen, and Peer Bork · 2016
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Toxcast chemical landscape: paving the road to 21st century toxicology
Ann M Richard, Richard S Judson, Keith A Houck, Christopher M Grulke, Patra Volarath, Inthirany Thillainadarajah, Chihae Yang, James Rathman, Matthew T Martin, John F Wambaugh, et al · 2016
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Conditional structure generation through graph variational generative adversarial nets
Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, and Pan Li · 2019
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Bayesian nonparametric federated learning of neural networks, 2019
Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald, Trong Nghia Hoang, and Yasaman Khazaeni · 2019
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Secure single-server aggregation with (poly) logarithmic overhead
James Henry Bell, Kallista A Bonawitz, Adrià Gascón, Tancrède Lepoint, and Mariana Raykova · 2020
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Tensorflow federated: Machine learning on decentralized data. 2020
K Bonawitz, H Eichner, W Grieskamp, et al · 2020
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Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, and Li Wang · 2020
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Secure aggregation with heterogeneous quantization in federated learning
Ahmed Roushdy Elkordy and A. Salman Avestimehr · 2020
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Fedner: Privacy-preserving medical named entity recognition with federated learning
Suyu Ge, Fangzhao Wu, Chuhan Wu, Tao Qi, Yongfeng Huang, and Xing Xie · 2020
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Federated visual classification with real-world data distribution
Tzu-Ming Harry Hsu, Hang Qi, and Matthew Brown · 2020
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Federated dynamic gnn with secure aggregation
Meng Jiang, Taeho Jung, Ryan Karl, and Tong Zhao · 2020
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Communication-efficient local stochastic gradient descent for scalable deep learning
S. Lee, Q. Kang, A. Agrawal, A. Choudhary, and W. k. Liao · 2020
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Basconv: Aggregating heterogeneous interactions for basket recommendation with graph convolutional neural network
Zhiwei Liu, Mengting Wan, Stephen Guo, Kannan Achan, and Philip S Yu · 2020
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Mitigating byzantine attacks in federated learning
Saurav Prakash and Amir Salman Avestimehr · 2020
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Adaptive federated optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečnỳ, Sanjiv Kumar, and H Brendan McMahan · 2020
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Privacy-preserving graph neural network for node classification
Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, and Li Wang · 2020
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Deep leakage from gradients
Ligeng Zhu and Song Han · 2020
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Understanding structural vulnerability in graph convolutional networks
Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, and Carl Yang · 2021
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Pubchem in 2021: new data content and improved web interfaces
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al · 2021
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Fednlp: A research platform for federated learning in natural language processing
Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, and Salman Avestimehr · 2021
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Dig: A turnkey library for diving into graph deep learning research
Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, et al · 2021
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Graph traversal with tensor functionals: A meta-algorithm for scalable learning, 2021
Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, and Aram Galstyan · 2021
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Cross-node federated graph neural network for spatio-temporal data modeling, 2021
Chuizheng Meng, Sirisha Rambhatla, and Yan Liu · 2021
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Fedgnn: Federated graph neural network for privacy-preserving recommendation
Chuhan Wu, Fangzhao Wu, Yang Cao, Yongfeng Huang, and Xing Xie · 2021
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Subgraph federated learning with missing neighbor generation, 2021
Ke Zhang, Carl Yang, Xiaoxiao Li, Lichao Sun, and Siu Ming Yiu · 2021
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