Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph
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Pedro A. Szekely | Xiang Ren | Meng Qu | Woojeong Jin | Changlin Zhang | Xiang Ren | Meng Qu | He Jiang | Tong Chen | Woojeong Jin | He Jiang | Changlin Zhang | Tong Chen
[1] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[2] Mathias Niepert,et al. Learning Sequence Encoders for Temporal Knowledge Graph Completion , 2018, EMNLP.
[3] Raia Hadsell,et al. Graph networks as learnable physics engines for inference and control , 2018, ICML.
[4] Julien Leblay,et al. Deriving Validity Time in Knowledge Graph , 2018, WWW.
[5] Jure Leskovec,et al. Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems , 2019, WWW.
[6] Jie Chen,et al. EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs , 2020, AAAI.
[7] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[8] Partha Talukdar,et al. HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding , 2018, EMNLP.
[9] Hongyuan Zha,et al. DyRep: Learning Representations over Dynamic Graphs , 2019, ICLR.
[10] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[11] Pascal Poupart,et al. Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey , 2019, ArXiv.
[12] Jason Weston,et al. Translating Embeddings for Modeling Multi-relational Data , 2013, NIPS.
[13] Jian-Yun Nie,et al. RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space , 2018, ICLR.
[14] Pasquale Minervini,et al. Convolutional 2D Knowledge Graph Embeddings , 2017, AAAI.
[15] Ryan A. Rossi,et al. Continuous-Time Dynamic Network Embeddings , 2018, WWW.
[16] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[17] Matthias Bethge,et al. A note on the evaluation of generative models , 2015, ICLR.
[18] Max Welling,et al. Modeling Relational Data with Graph Convolutional Networks , 2017, ESWC.
[19] Utkarsh Upadhyay,et al. Recurrent Marked Temporal Point Processes: Embedding Event History to Vector , 2016, KDD.
[20] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[21] Jure Leskovec,et al. Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks , 2019, KDD.
[22] Le Song,et al. Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs , 2017, ICML.
[23] Jure Leskovec,et al. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models , 2018, ICML.
[24] Fabian M. Suchanek,et al. YAGO3: A Knowledge Base from Multilingual Wikipedias , 2015, CIDR.
[25] Ole Winther,et al. Recurrent Relational Networks , 2017, NeurIPS.
[26] Zhiyuan Liu,et al. OpenKE: An Open Toolkit for Knowledge Embedding , 2018, EMNLP.
[27] Yueting Zhuang,et al. Dynamic Network Embedding by Modeling Triadic Closure Process , 2018, AAAI.
[28] Xavier Bresson,et al. Structured Sequence Modeling with Graph Convolutional Recurrent Networks , 2016, ICONIP.