| Conditional noise-contrastive estimation of unnormalised models C Ceylan, MU Gutmann International Conference on Machine Learning, 726-734, 2018 | 63 | 2018 |
| Learning node representations using stationary flow prediction on large payment and cash transaction networks C Ceylan, S Franzén, FT Pokorny International Conference on Machine Learning, 1395-1406, 2021 | 5 | 2021 |
| GraphDCA--a Framework for Node Distribution Comparison in Real and Synthetic Graphs C Ceylan, P Poklukar, H Hultin, A Kravchenko, A Varava, D Kragic arXiv preprint arXiv:2202.03884, 2022 | 3 | 2022 |
| Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs C Ceylan, K Ghoorchian, D Kragic arXiv preprint arXiv:2207.10149, 2022 | 2 | 2022 |
| Disobeying Directions: Switching Random Walk Filters for Unsupervised Node Embedding Learning on Directed Graphs C Ceylan, K Ghoorchian, D Kragic Transactions on Machine Learning Research 2025, 2025 | 1 | 2025 |
| Full-Rank Unsupervised Node Embeddings for Directed Graphs via Message Aggregation C Ceylan, K Ghoorchian, D Kragic Transactions on Machine Learning Research, 2025 | 1 | 2025 |
| Conditional Noise-Contrastive Estimation: With Application to Natural Image Statistics C Ceylan | 1 | 2017 |
| Towards Unsupervised, Analysable and Scalable Node Embedding Models for Transaction Networks C Ceylan KTH Royal Institute of Technology, 2025 | | 2025 |
| Scalable Unsupervised Feature Selection with Reconstruction Error Guarantees via QMR Decomposition C Ceylan, K Ghoorchian, D Kragic Proceedings of the 33rd ACM International Conference on Information and …, 2024 | | 2024 |
| GraphDCA-a Framework for Node Distribution Comparison in Real and Synthetic Graphs P Poklukar, C Ceylan, H Hultin, O Kravchenko, A Varava, D Kragic | | 2022 |
| Weight Matrix Adaptation for increased Memory Storage Capacity in a Spiking Hopfield Network C Ceylan, A Sunesson | | 2015 |
Danica KragicProfessor of Computer Science, KTH - Royal Institute of TechnologyVerified email at kth.se
