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Source localization is the inverse problem of graph information dissemination and has broad practical applications.
Reverse-time diffusion equation models
Brian DO Anderson · 1982
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Maximizing the spread of influence through a social network
David Kempe, Jon Kleinberg, and Eva Tardos · 2003
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Networks and epidemic models
Matt J Keeling and Ken TD Eames · 2005
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Spotting culprits in epidemics: How many and which ones?
B Aditya Prakash, Jilles Vreeken, and Christos Faloutsos · 2012
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A peek into the future: Predicting the evolution of popularity in user generated content
Mohamed Ahmed, Stella Spagna, Felipe Huici, and Saverio Niccolini · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Information source detection in the sir model: A sample-path-based approach
Kai Zhu and Lei Ying · 2014
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Multiple source detection without knowing the underlying propagation model
Zheng Wang, Chaokun Wang, Jisheng Pei, and Xiaojun Ye · 2017
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Catch’em all: Locating multiple diffusion sources in networks with partial observations
Kai Zhu, Zhen Chen, and Lei Ying · 2017
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Cascade dynamics modeling with attention-based recurrent neural network
Yongqing Wang, Huawei Shen, Shenghua Liu, Jinhua Gao, and Xueqi Cheng · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Multiple rumor source detection with graph convolutional networks
Ming Dong, Bolong Zheng, Nguyen Quoc Viet Hung, Han Su, and Guohui Li · 2019
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Position-aware graph neural networks
Jiaxuan You, Rex Ying, and Jure Leskovec · 2019
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Inf-vae: A variational autoencoder framework to integrate homophily and influence in diffusion prediction
Aravind Sankar, Xinyang Zhang, Adit Krishnan, and Jiawei Han · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Sliced score matching: A scalable approach to density and score estimation
Yang Song, Sahaj Garg, Jiaxin Shi, and Stefano Ermon · 2020
Geodiff: A geometric diffusion model for molecular conformation generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, and Jian Tang · 2021
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Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, and Roland Vollgraf · 2021
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Accurate learning of graph representations with graph multiset pooling
Jinheon Baek, Minki Kang, and Sung Ju Hwang · 2021
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H-diffu: Hyperbolic representations for information diffusion prediction
Shanshan Feng, Kaiqi Zhao, Lanting Fang, Kaiyu Feng, Wei Wei, Xutao Li, and Ling Shao · 2022
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An invertible graph diffusion neural network for source localization
Junxiang Wang, Junji Jiang, and Liang Zhao · 2022
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A multimodal variational encoder-decoder framework for micro-video popularity prediction
Jiayi Xie, Yaochen Zhu, Zhibin Zhang, Jian Peng, Jing Yi, Yaosi Hu, Hongyi Liu, and Zhenzhong Chen · 2020
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Deepis: Susceptibility estimation on social networks
Wenwen Xia, Yuchen Li, Jun Wu, and Shenghong Li · 2021
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Dydiff-vae: A dynamic variational framework for information diffusion prediction
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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A rapid source localization method in the early stage of large-scale network propagation
Zhen Wang, Dongpeng Hou, Chao Gao, Jiajin Huang, and Qi Xuan · 2022
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Source localization of graph diffusion via variational autoencoders for graph inverse problems
Chen Ling, Junji Jiang, Junxiang Wang, and Zhao Liang · 2022
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Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael T Mccann, Marc L Klasky, and Jong Chul Ye · 2022
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Score-based generative modeling of graphs via the system of stochastic differential equations
Jaehyeong Jo, Seul Lee, and Sung Ju Hwang · 2022
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Ms-hgat: Memory-enhanced sequential hypergraph attention network for information diffusion prediction
Ling Sun, Yuan Rao, Xiangbo Zhang, Yuqian Lan, and Shuanghe Yu · 2022
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