@inproceedings{DBLP:conf/www/XuSX022,

title = {Time-aware Entity Alignment using Temporal Relational Attention},

author = {Chengjin Xu and 

 Fenglong Su and 

 Bo Xiong and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2022/webconf_temporal_entity_alignment.pdf},

doi = {10.1145/3485447.3511922},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, 

 April 25 - 29, 2022},

pages = {788--797},

publisher = {ACM},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ijcai/AliB0T0T022,

title = {Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract)},

author = {Mehdi Ali and 

 Max Berrendorf and 

 Mikhail Galkin and 

 Veronika Thost and 

 Tengfei Ma and 

 Volker Tresp and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2022/ijcai_inductive_link_prediction.pdf},

doi = {10.24963/ijcai.2022/731},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Proceedings of the Thirty-First International Joint Conference on 

 Artificial Intelligence, IJCAI 2022, Vienna, Austria, 23-29 July 

 2022},

pages = {5259--5263},

publisher = {ijcai.org},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/esws/NayyeriVKAWBL22,

title = {Dihedron Algebraic Embeddings for Spatio-Temporal Knowledge Graph Completion},

author = {Mojtaba Nayyeri and 

 Sahar Vahdati and 

 Md Tansen Khan and 

 Mirza Mohtashim Alam and 

 Lisa Wenige and 

 Andreas Behrend and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2022/eswc_spatiotemporal_kge.pdf},

doi = {10.1007/978-3-031-06981-9_15},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {The Semantic Web - 19th International Conference, ESWC 2022, Hersonissos, 

 Crete, Greece, May 29 - June 2, 2022, Proceedings},

volume = {13261},

pages = {253--269},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/aaai/NayyeriVA021,

title = {5* Knowledge Graph Embeddings with Projective Transformations},

author = {Mojtaba Nayyeri and Sahar Vahdati and Can Aykul and Jens Lehmann},

url = {https://ojs.aaai.org/index.php/AAAI/article/view/17095

https://jens-lehmann.org/files/2021/aaai_5StarE.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 

 2021, Thirty-Third Conference on Innovative Applications of Artificial 

 Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances 

 in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 

 2021},

pages = {9064--9072},

publisher = {AAAI Press},

keywords = {Representation Learning in Knowledge Graphs, Top Publications},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/pakdd/NayyeriXYVAY021,

title = {Loss-Aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models},

author = {Mojtaba Nayyeri and Chengjin Xu and Yadollah Yaghoobzadeh and Sahar Vahdati and Mirza Mohtashim Alam and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2021/pakdd_kge_loss_wrong_claims.pdf},

doi = {10.1007/978-3-030-75768-7_7},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Advances in Knowledge Discovery and Data Mining - 25th Pacific-Asia 

 Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, 

 Part III},

volume = {12714},

pages = {77--89},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ecir/NayyeriVSAYL21,

title = {Pattern-Aware and Noise-Resilient Embedding Models},

author = {Mojtaba Nayyeri and Sahar Vahdati and Emanuel Sallinger and Mirza Mohtashim Alam and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2021/ecir_kgrl_patterns_noise.pdf},

doi = {10.1007/978-3-030-72113-8_32},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Advances in Information Retrieval - 43rd European Conference on IR 

 Research, ECIR 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, 

 Part I},

volume = {12656},

pages = {483--496},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/naacl/XuCNL21,

title = {Temporal Knowledge Graph Completion using a Linear Temporal Regularizer  and Multivector Embeddings},

author = {Chengjin Xu and Yung-Yu Chen and Mojtaba Nayyeri and Jens Lehmann},

url = {https://www.aclweb.org/anthology/2021.naacl-main.202/

https://jens-lehmann.org/files/2021/naacl_temporal_kge_multivector.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {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},

pages = {2569--2578},

publisher = {Association for Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/pkdd/SadeghiCGL21,

title = {Embedding Knowledge Graphs Attentive to Positional and Centrality  Qualities},

author = {Afshin Sadeghi and 

 Diego Collarana and 

 Damien Graux and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2021/ecml_kge_attentive_pc_qualities.pdf},

doi = {10.1007/978-3-030-86520-7_34},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Machine Learning and Knowledge Discovery in Databases. Research Track 

 - European Conference, ECML PKDD 2021, Bilbao, Spain, September 

 13-17, 2021, Proceedings, Part II},

volume = {12976},

pages = {548--564},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ijcnn/XuNVL21,

title = {Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph  Embeddings},

author = {Chengjin Xu and 

 Mojtaba Nayyeri and 

 Sahar Vahdati and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2021/ijcnn_kge_lowdim.pdf},

doi = {10.1109/IJCNN52387.2021.9533372},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen, 

 China, July 18-22, 2021},

pages = {1--8},

publisher = {IEEE},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/emnlp/XuS021,

title = {Time-aware Graph Neural Network for Entity Alignment between Temporal  Knowledge Graphs},

author = {Chengjin Xu and 

 Fenglong Su and 

 Jens Lehmann},

url = {https://aclanthology.org/2021.emnlp-main.709

https://jens-lehmann.org/files/2021/emnlp_tkge_gnn.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural 

 Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican 

 Republic, 7-11 November, 2021},

pages = {8999--9010},

publisher = {Association for Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/emnlp/NayyeriXHA0V21,

title = {Knowledge Graph Representation Learning using Ordinary Differential  Equations},

author = {Mojtaba Nayyeri and 

 Chengjin Xu and 

 Franca Hoffmann and 

 Mirza Mohtashim Alam and 

 Jens Lehmann and 

 Sahar Vahdati},

url = {https://aclanthology.org/2021.emnlp-main.750

https://jens-lehmann.org/files/2021/emnlp_fielde.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural 

 Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican 

 Republic, 7-11 November, 2021},

pages = {9529--9548},

publisher = {Association for Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/AliB0TMT021,

title = {Improving Inductive Link Prediction Using Hyper-relational Facts},

author = {Mehdi Ali and 

 Max Berrendorf and 

 Mikhail Galkin and 

 Veronika Thost and 

 Tengfei Ma and 

 Volker Tresp and 

 Jens Lehmann},

url = {https://jens-lehmann.org/files/2021/iswc_inductive_kge.pdf},

doi = {10.1007/978-3-030-88361-4_5},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, 

 ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings},

volume = {12922},

pages = {74--92},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/i-semantics/SadeghiSS021,

title = {BenchEmbedd: A FAIR Benchmarking tool for Knowledge Graph Embeddings},

author = {Afshin Sadeghi and 

 Xhulia Shahini and 

 Martin Schmitz and 

 Jens Lehmann},

url = {http://ceur-ws.org/Vol-2941/paper14.pdf

https://jens-lehmann.org/files/2021/semantics_pd_benchembedd.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Joint Proceedings of the Semantics co-located events: Poster&Demo 

 track and Workshop on Ontology-Driven Conceptual Modelling of Digital 

 Twins co-located with Semantics 2021, Amsterdam and Online, September 

 6-9, 2021},

volume = {2941},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/dexa/RivasGCLV20,

title = {Unveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings},

author = {Ariam Rivas and Irl\'{a}n Grangel-Gonz\'{a}lez and Diego Collarana and Jens Lehmann and Maria-Esther Vidal},

url = {https://jens-lehmann.org/files/2021/dexa_i4.0_kge.pdf},

doi = {10.1007/978-3-030-59051-2_12},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Database and Expert Systems Applications - 31st International Conference, 

 DEXA 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings, 

 Part II},

volume = {12392},

pages = {179--194},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/esws/AlamJAM020,

title = {Affinity Dependent Negative Sampling for Knowledge Graph Embeddings},

author = {Mirza Mohtashim Alam and Hajira Jabeen and Mehdi Ali and Karishma Mohiuddin and Jens Lehmann},

url = {http://ceur-ws.org/Vol-2635/paper8.pdf},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Proceedings of the Workshop on Deep Learning for Knowledge Graphs 

 (DL4KG2020) co-located with the 17th Extended Semantic Web Conference 

 2020 (ESWC 2020), Heraklion, Greece, June 02, 2020 - moved online},

volume = {2635},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/esws/NayyeriVZY020,

title = {Embedding-Based Recommendations on Scholarly Knowledge Graphs},

author = {Mojtaba Nayyeri and Sahar Vahdati and Xiaotian Zhou and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/eswc_kge_scholarly.pdf},

doi = {10.1007/978-3-030-49461-2_15},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {The Semantic Web - 17th International Conference, ESWC 2020, Heraklion, 

 Crete, Greece, May 31-June 4, 2020, Proceedings},

volume = {12123},

pages = {255--270},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/NayyeriXVVSYL20,

title = {Fantastic Knowledge Graph Embeddings and How to Find the Right Space for Them},

author = {Mojtaba Nayyeri and Chengjin Xu and Sahar Vahdati and Nadezhda Vassilyeva and Emanuel Sallinger and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/iswc_kge_solution_spaces.pdf},

doi = {10.1007/978-3-030-62419-4_25},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {The Semantic Web - ISWC 2020 - 19th International Semantic Web Conference, 

 Athens, Greece, November 2-6, 2020, Proceedings, Part I},

volume = {12506},

pages = {438--455},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/coling/XuNCL20,

title = {Knowledge Graph Embeddings in Geometric Algebras},

author = {Chengjin Xu and Mojtaba Nayyeri and Yung-Yu Chen and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/coling_kge_geometric_algebras.pdf},

doi = {10.18653/v1/2020.coling-main.46},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Proceedings of the 28th International Conference on Computational 

 Linguistics, COLING 2020, Barcelona, Spain (Online), December 8-13, 

 2020},

pages = {530--544},

publisher = {International Committee on Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ijcnn/NayyeriZVIY020,

title = {Let the Margin SlidE for Knowledge Graph Embeddings via a Correntropy Objective Function},

author = {Mojtaba Nayyeri and Xiaotian Zhou and Sahar Vahdati and Reza Izanloo and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/ijcnn_kge_adaptive_margin.pdf},

doi = {10.1109/IJCNN48605.2020.9207513},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {2020 International Joint Conference on Neural Networks, IJCNN 2020, 

 Glasgow, United Kingdom, July 19-24, 2020},

pages = {1--9},

publisher = {IEEE},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ecai/SadeghiGY020,

title = {MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs},

author = {Afshin Sadeghi and Damien Graux and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/ecai_kge_mde.pdf},

doi = {10.3233/FAIA200248},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {ECAI 2020 - 24th European Conference on Artificial Intelligence, 

 29 August-8 September 2020, Santiago de Compostela, Spain, August 

 29 - September 8, 2020 - Including 10th Conference on Prestigious 

 Applications of Artificial Intelligence (PAIS 2020)},

volume = {325},

pages = {1427--1434},

publisher = {IOS Press},

series = {Frontiers in Artificial Intelligence and Applications},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/emnlp/GalkinTMUL20,

title = {Message Passing for Hyper-Relational Knowledge Graphs},

author = {Mikhail Galkin and Priyansh Trivedi and Gaurav Maheshwari and Ricardo Usbeck and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/emnlp_hyperrelational_message_passing.pdf},

doi = {10.18653/v1/2020.emnlp-main.596},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural 

 Language Processing, EMNLP 2020, Online, November 16-20, 2020},

pages = {7346--7359},

publisher = {Association for Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/XuNAYL20,

title = {Temporal Knowledge Graph Completion Based on Time Series Gaussian Embedding},

author = {Chenjin Xu and Mojtaba Nayyeri and Fouad Alkhoury and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/iswc_kge_gaussian.pdf},

doi = {10.1007/978-3-030-62419-4_37},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {The Semantic Web - ISWC 2020 - 19th International Semantic Web Conference, 

 Athens, Greece, November 2-6, 2020, Proceedings, Part I},

volume = {12506},

pages = {654--671},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/coling/XuNAYL20,

title = {TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation},

author = {Chengjin Xu and Mojtaba Nayyeri and Fouad Alkhoury and Hamed Shariat Yazdi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2020/coling_tero.pdf},

doi = {10.18653/v1/2020.coling-main.139},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Proceedings of the 28th International Conference on Computational 

 Linguistics, COLING 2020, Barcelona, Spain (Online), December 8-13, 

 2020},

pages = {1583--1593},

publisher = {International Committee on Computational Linguistics},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/pkdd/Sadeghi019,

title = {Linking Physicians to Medical Research Results via Knowledge Graph Embeddings and Twitter},

author = {Afshin Sadeghi and Jens Lehmann},

url = {https://jens-lehmann.org/files/2019/ecml_sogood_physicians.pdf},

doi = {10.1007/978-3-030-43823-4_49},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {Machine Learning and Knowledge Discovery in Databases - International 

 Workshops of ECML PKDD 2019, W\"{u}rzburg, Germany, September 

 16-20, 2019, Proceedings, Part I},

volume = {1167},

pages = {622--630},

publisher = {Springer},

series = {Communications in Computer and Information Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/AliHD019,

title = {Predicting Missing Links Using PyKEEN},

author = {Mehdi Ali and Charles Tapley Hoyt and Daniel Domingo-Fern\'{a}ndez and Jens Lehmann},

url = {http://ceur-ws.org/Vol-2456/paper64.pdf 

https://jens-lehmann.org/files/2019/iswc_pd_pykeen.pdf},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, 

 Industry, and Outrageous Ideas) co-located with 18th International 

 Semantic Web Conference (ISWC 2019), Auckland, New Zealand, October 

 26-30, 2019},

volume = {2456},

pages = {245--248},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/AliJH019,

title = {The KEEN Universe - An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability},

author = {Mehdi Ali and Hajira Jabeen and Charles Tapley Hoyt and Jens Lehmann},

url = {https://jens-lehmann.org/files/2019/iswc_keen_universe.pdf},

doi = {10.1007/978-3-030-30796-7_1},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, 

 Auckland, New Zealand, October 26-30, 2019, Proceedings, Part II},

volume = {11779},

pages = {3--18},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Representation Learning in Knowledge Graphs},

pubstate = {published},

tppubtype = {inproceedings}

}