Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification. - Ruud van Bakel; Teodor Aleksiev; Daniel Daza; Dimitrios Alivanistos; Michael Cochez (GKR, 2020)

Message Passing for Query Answering over Knowledge Graphs. - Daniel Daza; Michael Cochez (CoRR, 2020)

Complex Query Answering with Neural Link Predictors. - Erik Arakelyan; Daniel Daza; Pasquale Minervini; Michael Cochez (ICLR, 2021)

Inductive Entity Representations from Text via Link Prediction. - Daniel Daza; Michael Cochez; Paul Groth (WWW, 2021)

Inductive WN18RR and FB15k-237. - Daniel Daza; Michael Cochez; Paul Groth (Zenodo, 2021)

SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning. - Daniel Daza; Michael Cochez; Paul Groth (SPNLP@ACL, 2022)

Complex Query Answering with Neural Link Predictors (Extended Abstract). - Pasquale Minervini; Erik Arakelyan; Daniel Daza; Michael Cochez (IJCAI, 2022)

Reasoning beyond Triples: Recent Advances in Knowledge Graph Embeddings. - Bo Xiong; Mojtaba Nayyeri; Daniel Daza; Michael Cochez (CIKM, 2023)

Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. - Erik Arakelyan; Pasquale Minervini; Daniel Daza; Michael Cochez; Isabelle Augenstein (NeurIPS, 2023)

Harnessing the Web and Knowledge Graphs for Automated Impact Investing Scoring. - Qingzhi Hu; Daniel Daza; Laurens Swinkels; Kristina Usaite; Robbert-Jan 't Hoen; Paul Groth (CoRR, 2023)

Approximate Answering of Graph Queries. - Michael Cochez; Dimitrios Alivanistos; Erik Arakelyan; Max Berrendorf; Daniel Daza; Mikhail Galkin 001; Pasquale Minervini; Mathias Niepert; Hongyu Ren (CoRR, 2023)

Approximate Answering of Graph Queries. - Michael Cochez; Dimitrios Alivanistos; Erik Arakelyan; Max Berrendorf; Daniel Daza; Mikhail Galkin 001; Pasquale Minervini; Mathias Niepert; Hongyu Ren (Compendium of Neurosymbolic Artificial Intelligence, 2023)

BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. - Daniel Daza; Dimitrios Alivanistos; Payal Mitra; Thom Pijnenburg; Michael Cochez; Paul Groth (J. Biomed. Semant., 2023)

UnRavL: A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs. - Tamara Cucumides; Daniel Daza; Pablo Barceló; Michael Cochez; Floris Geerts; Juan L. Reutter; Miguel Romero 001 (LoG, 2024)

Explaining Graph Neural Networks for Node Similarity on Graphs. - Daniel Daza; Cuong Xuan Chu; Trung-Kien Tran; Daria Stepanova 001; Michael Cochez; Paul Groth (CoRR, 2024)

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. - Taraneh Younesian; Daniel Daza; Emile van Krieken; Thiviyan Thanapalasingam; Peter Bloem (Trans. Mach. Learn. Res., 2025)

EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge. - Klim Zaporojets; Daniel Daza; Edoardo Barba; Ira Assent; Roberto Navigli; Paul Groth (CoRR, 2025)

Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints. - Daniel Daza; Alberto Bernardi; Luca Costabello; Christophe Guéret; Masoud Mansoury; Michael Cochez; Martijn Schut (CoRR, 2025)