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2020 – today
- 2024
[i9]Daniel Daza, Cuong Xuan Chu, Trung-Kien Tran, Daria Stepanova, Michael Cochez, Paul Groth:
Explaining Graph Neural Networks for Node Similarity on Graphs. CoRR abs/2407.07639 (2024)- 2023
- [j1]Daniel Daza
, Dimitrios Alivanistos, Payal Mitra, Thom Pijnenburg, Michael Cochez, Paul Groth:
BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. J. Biomed. Semant. 14(1): 20 (2023) - [c7]Bo Xiong, Mojtaba Nayyeri, Daniel Daza, Michael Cochez:
Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings. CIKM 2023: 5228-5231 - [c6]Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein:
Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. NeurIPS 2023 - [p1]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. Compendium of Neurosymbolic Artificial Intelligence 2023: 373-386 - [i8]Daniel Daza, Dimitrios Alivanistos, Payal Mitra, Thom Pijnenburg, Michael Cochez, Paul Groth:
BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs. CoRR abs/2306.03606 (2023) - [i7]Qingzhi Hu, Daniel Daza, Laurens Swinkels, Kristina Usaite, Robbert-Jan 't Hoen, Paul Groth:
Harnessing the Web and Knowledge Graphs for Automated Impact Investing Scoring. CoRR abs/2308.02622 (2023) - [i6]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. CoRR abs/2308.06585 (2023) - [i5]Taraneh Younesian, Thiviyan Thanapalasingam, Emile van Krieken, Daniel Daza, Peter Bloem:
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. CoRR abs/2310.03399 (2023) - 2022
- [c5]Daniel Daza, Michael Cochez, Paul Groth:
SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning. SPNLP@ACL 2022: 32-39 - [c4]Pasquale Minervini, Erik Arakelyan, Daniel Daza, Michael Cochez:
Complex Query Answering with Neural Link Predictors (Extended Abstract). IJCAI 2022: 5309-5313 - 2021
- [c3]Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez:
Complex Query Answering with Neural Link Predictors. ICLR 2021 - [c2]Daniel Daza, Michael Cochez, Paul Groth:
Inductive Entity Representations from Text via Link Prediction. WWW 2021: 798-808 - [d1]Daniel Daza, Michael Cochez, Paul Groth:
Inductive WN18RR and FB15k-237. Zenodo, 2021
- [i4]Ruud van Bakel, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, Michael Cochez:
Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification. CoRR abs/2102.11389 (2021) - 2020
- [c1]Ruud van Bakel, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, Michael Cochez:
Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification. GKR 2020: 107-124 - [i3]Daniel Daza, Michael Cochez:
Message Passing for Query Answering over Knowledge Graphs. CoRR abs/2002.02406 (2020) - [i2]Daniel Daza, Michael Cochez, Paul Groth:
Inductive Entity Representations from Text via Link Prediction. CoRR abs/2010.03496 (2020) - [i1]Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez:
Complex Query Answering with Neural Link Predictors. CoRR abs/2011.03459 (2020)
Coauthor Index
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