Ismail Ilkan Ceylan
My research interests are broadly in AI & machine learning with a particular focus on relational learning & reasoning, which includes a class of challenging problems that can be naturally characterised on relational structures, such as graphs, knowledge bases, or more general logical representations. The goal is being able to more efficiently and reliably learn from relational patterns and reason over them. This is a highly interactive field, where techniques from machine learning (e.g., deep learning, graph representation learning, probabilistic inference), knowledge representation (e.g., logical reasoning), and theoretical computer science (complexity theory, graph theory) are relevant.
Note: If you are interested in applying for a DPhil, please get in touch beforehand.
The Dichotomy of Evaluating Homomorphism−Closed Queries on Probabilistic Graphs
Antoine Amarilli and İsmail İlkan Ceylan
In Logical Methods in Computer Science. Vol. 18/1. 2022.
Temporal Knowledge Graph Completion using Box Embeddings
Johannes Messner‚ Ralph Abboud and İsmail İlkan Ceylan
In Proceedings of the 36th AAAI Conference on Artificial Intelligence‚ AAAI 2022‚ Vancouver‚ BC‚ Canada. AAAI Press. 2022.
Equivariant Quantum Graph Circuits
Peter Mérnyei‚ Konstantinos Meichanetzidis and İsmail İlkan Ceylan
In Proceedings of the 39th International Conference on Machine Learning‚ ICML 2022‚ Baltimore‚ Maryland‚ USA. 2022.