Chengjin Xu left SDA. The profile below reflects the status at the point of his departure and is no longer updated.
PhD Student
Computer Science Institute
University of Bonn
Profiles: LinkedIn
Room 1.052
Endenicher Allee 19a, 53115 Bonn
University of Bonn, Computer Science
soledad921@gmail.com
Short CV
Chengjin Xu is a PhD Student at the University of Bonn. Chengjin’s research interests are in the area of Knowledge Embedding and Machine Learning.
Publications
2022
Ultrahyperbolic Knowledge Graph Embeddings Inproceedings
In: KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022, pp. 2130–2139, ACM, 2022.
Time-aware Entity Alignment using Temporal Relational Attention Inproceedings
In: WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022, pp. 788–797, ACM, 2022.
2021
Knowledge Graph Representation Learning using Ordinary Differential Equations Inproceedings
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021, pp. 9529–9548, Association for Computational Linguistics, 2021.
Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs Inproceedings
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021, pp. 8999–9010, Association for Computational Linguistics, 2021.
Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings Inproceedings
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, Online, June 6-11, 2021, pp. 2569–2578, Association for Computational Linguistics, 2021.
Loss-Aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models Inproceedings
In: Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part III, pp. 77–89, Springer, 2021.
2020
TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation Inproceedings
In: Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8-13, 2020, pp. 1583–1593, International Committee on Computational Linguistics, 2020.
Knowledge Graph Embeddings in Geometric Algebras Inproceedings
In: Proceedings of the 28th International Conference on Computational Linguistics, COLING 2020, Barcelona, Spain (Online), December 8-13, 2020, pp. 530–544, International Committee on Computational Linguistics, 2020.
The Effect of Rule Injectionin a Leakage Free Dataset Inproceedings
In: Proceedings of the International Workshop on Knowledge Representation and Representation Learning co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020), Virtual Event, September, 2020, pp. 28–35, CEUR-WS.org, 2020.
Multiple Run Ensemble Learning with Low Dimensional Knowledge Graph Embeddings Inproceedings
In: Proceedings of the International Workshop on Knowledge Representation and Representation Learning co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020), Virtual Event, September, 2020, pp. 36–42, CEUR-WS.org, 2020.
Fantastic Knowledge Graph Embeddings and How to Find the Right Space for Them Inproceedings
In: The Semantic Web - ISWC 2020 - 19th International Semantic Web Conference, Athens, Greece, November 2-6, 2020, Proceedings, Part I, pp. 438–455, Springer, 2020.