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Graph Neural Networks (GNNs) have recently become increasingly popular due to their ability to learn complex systems of relations or interactions arising in a broad spectrum of problems ranging from biology and particle physics to social networks and recommendation systems.
Fake news detection on social media using geometric deep learning
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, and Michael M. Bronstein · 1902
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Time2vec: Learning a vector representation of time
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali, Janahan Ramanan, Jaspreet Sahota, Sanjay Thakur, Stella Wu, Cathal Smyth, Pascal Poupart, and Marcus Brubaker · 1907
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Long short-term memory
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The link-prediction problem for social networks
David Liben-Nowell and Jon Kleinberg · 2007
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Temporal-relational classifiers for prediction in evolving domains
Umang Sharan and Jennifer Neville · 2008
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The time-series link prediction problem with applications in communication surveillance
Zan Huang and Dennis KJ Lin · 2009
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A particle-and-density based evolutionary clustering method for dynamic networks
Min-Soo Kim and Jiawei Han · 2009
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Temporal link prediction using matrix and tensor factorizations
Daniel M Dunlavy, Tamara G Kolda, and Evrim Acar · 2011
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Evolutionary clustering and analysis of bibliographic networks
Manish Gupta, Charu C Aggarwal, Jiawei Han, and Yizhou Sun · 2011
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Time series based link prediction
Paulo Ricardo da Silva Soares and Ricardo Bastos Cavalcante Prudêncio · 2012
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A hybrid time-series link prediction framework for large social network
Jia Zhu, Qing Xie, and Eun Jung Chin · 2012
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Deepwalk: Online learning of social representations
Bryan Perozzi, Rami Al-Rfou, and Steven Skiena · 2014
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarelli, Timothy Hirzel, Alan Aspuru-Guzik, and Ryan P Adams · 2015
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Link prediction in dynamic social networks by integrating different types of information
Nahla Mohamed Ahmed Ibrahim and Ling Chen · 2015
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An efficient algorithm for link prediction in temporal uncertain social networks
Nahla Mohamed Ahmed and Ling Chen · 2016
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Sampling-based algorithm for link prediction in temporal networks
Nahla Mohamed Ahmed, Ling Chen, Yulong Wang, Bin Li, Yun Li, and Wei Liu · 2016
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Interaction networks for learning about objects, relations and physics
Peter W Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, et al · 2016
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Node2vec: Scalable feature learning for networks
Aditya Grover and Jure Leskovec · 2016
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Link prediction using time series of neighborhood-based node similarity scores
İsmail Güneş, Şule Gündüz-Öğüdücü, and Zehra Çataltepe · 2016
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Variational graph auto-encoders
Thomas N Kipf and Max Welling · 2016
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Geometric deep learning on graphs and manifolds using mixture model cnns
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, and Michael M. Bronstein · 2016
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Node classification in dynamic social networks
Yulong Pei, Jianpeng Zhang, GH Fletcher, and Mykola Pechenizkiy · 2016
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An adaptive random walk sampling method on dynamic community detection
Yu Xin, Zhi-Qiang Xie, and Jing Yang · 2016
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Link prediction based on common-neighbors for dynamic social network
Lin Yao, Luning Wang, Lv Pan, and Kai Yao · 2016
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Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
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Semi-Supervised Classification with Graph Convolutional Networks
Thomas N. Kipf and Max Welling · 2017
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A novel time series link prediction method: Learning automata approach
Behnaz Moradabadi and Mohammad Reza Meybodi · 2017
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Know-evolve: Deep temporal reasoning for dynamic knowledge graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Link prediction with spatial and temporal consistency in dynamic networks
Wenchao Yu, Wei Cheng, Charu C Aggarwal, Haifeng Chen, and Wei Wang · 2017
Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, and Jure Leskovec · 2018
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Netwalk: A flexible deep embedding approach for anomaly detection in dynamic networks
Wenchao Yu, Wei Cheng, Charu C Aggarwal, Kai Zhang, Haifeng Chen, and Wei Wang · 2018
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Gaan: Gated attention networks for learning on large and spatiotemporal graphs
Jiani Zhang, Xingjian Shi, Junyuan Xie, Hao Ma, Irwin King, and Dit-Yan Yeung · 2018
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Link prediction based on graph neural networks
Muhan Zhang and Yixin Chen · 2018
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Dynamic network embedding by modeling triadic closure process
Lekui Zhou, Yang Yang, Xiang Ren, Fei Wu, and Yueting Zhuang · 2018
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Modeling polypharmacy side effects with graph convolutional networks
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What to do next: Modeling user behaviors by time-lstm
Yu Zhu, Hao Li, Yikang Liao, Beidou Wang, Ziyu Guan, Haifeng Liu, and Deng Cai · 2017
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Relational inductive biases, deep learning, and graph networks
Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, and Ryan Faulkner · 2018
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Gc-lstm: Graph convolution embedded lstm for dynamic link prediction
Jinyin Chen, Xuanheng Xu, Yangyang Wu, and Haibin Zheng · 2018
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Graph neural networks for icecube signal classification
Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer Klein, and Joan Bruna · 2018
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HyTE: Hyperplane-based temporally aware knowledge graph embedding
Shib Sankar Dasgupta, Swayambhu Nath Ray, and Partha Talukdar · 2018
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Combining temporal aspects of dynamic networks with node2vec for a more efficient dynamic link prediction
S. De Winter, T. Decuypere, S. Mitrović, B. Baesens, and J. De Weerdt · 2018
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Marinka Zitnik, Monica Agrawal, and Jure Leskovec · 2018
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evolve2vec: Learning network representations using temporal unfolding
Nikolaos Bastas, Theodoros Semertzidis, Apostolos Axenopoulos, and Petros Daras · 2019
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Relationship prediction in dynamic heterogeneous information networks
Amin Milani Fard, Ebrahim Bagheri, and Ke Wang · 2019
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Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
Pablo Gainza et al · 2019
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Diachronic embedding for temporal knowledge graph completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker, and Pascal Poupart · 2019
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Predicting dynamic embedding trajectory in temporal interaction networks
Srijan Kumar, Xikun Zhang, and Jure Leskovec · 2019
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Embedding models for episodic knowledge graphs
Yunpu Ma, Volker Tresp, and Erik A Daxberger · 2019
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Evolvegcn: Evolving graph convolutional networks for dynamic graphs
Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, and Charles E Leisersen · 2019
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ncrna classification with graph convolutional networks
Emanuele Rossi, Federico Monti, Michael M. Bronstein, and Pietro Liò · 2019
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Node embedding over temporal graphs
Uriel Singer, Ido Guy, and Kira Radinsky · 2019
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Dyrep: Learning representations over dynamic graphs
Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, and Hongyuan Zha · 2019
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Hyperfoods: Machine intelligent mapping of cancer-beating molecules in foods
Kirill Veselkov et al · 2019
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew · 2019
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Temporal knowledge graph completion based on time series gaussian embedding
Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Jens Lehmann, and Hamed Shariat Yazdi · 2019
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Bing Yu, Mengzhang Li, Jiyong Zhang, and Zhanxing Zhu · 2019
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Privacy-preserving recommender systems challenge on twitter’s home timeline
Luca Belli, Sofia Ira Ktena, Alykhan Tejani, Alexandre Lung-Yut-Fon, Frank Portman, Xiao Zhu, Yuanpu Xie, Akshay Gupta, Michael M. Bronstein, Amra Delić, et al · 2020
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Representation learning for dynamic graphs: A survey
Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, and Pascal Poupart · 2020
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Dynamic graph convolutional networks
Franco Manessi, Alessandro Rozza, and Mario Manzo · 2020
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Sign: Scalable inception graph neural networks
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Dysat: Deep neural representation learning on dynamic graphs via self-attention networks
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Inductive representation learning on temporal graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan · 2020
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