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
Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion Journal Article
In: CoRR, vol. abs/2202.09464, 2022.
Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs Journal Article
In: CoRR, vol. abs/2203.02150, 2022.
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.
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph Embeddings Journal Article
In: CoRR, vol. abs/2104.05003, 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.
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.
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.
Motif Learning in Knowledge Graphs Using Ŧrajectories Of Đifferential Equations Journal Article
In: CoRR, vol. abs/2010.06684, 2020.
2019
LogicENN: A Neural Based Knowledge Graphs Embedding Model with Logical Rules Journal Article
In: CoRR, vol. abs/1908.07141, 2019.
On the Knowledge Graph Completion Using Translation Based Embedding: The Loss Is as Important as the Score Journal Article
In: CoRR, vol. abs/1909.00519, 2019.
Ŧemporal Knowledge Graph Embedding Model based on Additive Ŧime Series Đecomposition Journal Article
In: CoRR, vol. abs/1911.07893, 2019.