Recent Activity
- Our paper, SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning has been presented at the ACL 2020 Workshop on Structured Prediction for NLP.
- I've presented Inductive Entity Representations from Text via Link Prediction at the Web Conference 2021.
- Our paper, Complex Query Answering with Neural Link Predictors, has received an Outsdanding Paper Award at ICLR 2021! (see announcement.)
- New blogpost on Normalizing Flows.
- I've written a report for my virtual attendance to AKBC 2020.
- Our paper, Message Passing Query Embedding, has been accepted at the ICML 2020 GRL+ Workshop!
- I have obtained my MSc degree in Artificial Intelligence from the University of Amsterdam, with distinction cum laude. In my thesis I worked on the topic of graph representation learning, under the supervision of a Thomas Kipf.
- I have presented my MSc thesis at UCL in London, at the Workshop on graphs for machine learning and sequential decision making. See my poster here.
- I attended the TomTom AI summer school. We even got to train our own self-driving car! Some thoughts and pictures on LinkedIn.
- New blog post on computing optimal transport costs with PyTorch.
Publications
Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez, in ICLR 2021 (Outstanding Paper Award).
[arXiv] [code] [bibtex]
Inductive Entity Representations from Text via Link Prediction
Daniel Daza, Michael Cochez, and Paul Groth, in The Web Conference 2021.
[arXiv] [code] [bibtex]
Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification
Ruud van Bakel, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, and Michael Cochez, in International Workshop on Graph Structures for Knowledge Representation and Reasoning, 2020.
[arXiv] [bibtex]
Message Passing Query Embedding
Daniel Daza and Michael Cochez, in ICLR 2020 Workshop on Graph Representation Learning and Beyond.
[arXiv] [code] [bibtex]
A Modular Framework for Unsupervised Graph Representation Learning
Daniel Daza, Master's Thesis (2019), supervisor: Thomas Kipf.
[pdf]