| The option keyboard: Combining skills in reinforcement learning A Barreto, D Borsa, S Hou, G Comanici, E Aygün, P Hamel, D Toyama, ... Advances in Neural Information Processing Systems 32, 2019 | 117 | 2019 |
| Learning to cooperate: Emergent communication in multi-agent navigation I Kajić, E Aygün, D Precup arXiv preprint arXiv:2004.01097, 2020 | 33 | 2020 |
| An improvement of centroid-based classification algorithm for text classification Z Cataltepe, E Aygun 2007 IEEE 23rd International Conference on Data Engineering Workshop, 952-956, 2007 | 28 | 2007 |
| Proving theorems using incremental learning and hindsight experience replay E Aygün, A Anand, L Orseau, X Glorot, SM Mcaleer, V Firoiu, LM Zhang, ... International Conference on Machine Learning, 1198-1210, 2022 | 24 | 2022 |
| Spectral renormalization group theory on networks E Aygün, A Erzan Journal of Physics: Conference Series 319 (1), 012007, 2011 | 21 | 2011 |
| Learning to prove from synthetic theorems E Aygün, Z Ahmed, A Anand, V Firoiu, X Glorot, L Orseau, D Precup, ... arXiv preprint arXiv:2006.11259, 2020 | 20 | 2020 |
| Training a first-order theorem prover from synthetic data V Firoiu, E Aygun, A Anand, Z Ahmed, X Glorot, L Orseau, L Zhang, ... arXiv preprint arXiv:2103.03798, 2021 | 18 | 2021 |
| A formal treatment of generalized preferential attachment and its empirical validation A Herdağdelen, E Aygün, H Bingol Europhysics Letters 78 (6), 60007, 2007 | 15 | 2007 |
| Learning representations of logical formulae using graph neural networks X Glorot, A Anand, E Aygun, S Mourad, P Kohli, D Precup Neural Information Processing Systems, Workshop on Graph Representation Learning, 2019 | 14 | 2019 |
| Knowledge representation for reinforcement learning using general value functions G Comanici, D Precup, A Barreto, DK Toyama, E Aygün, P Hamel, ... | 11 | 2018 |
| Systems and methods for measuring media performance on end-user devices E Aygun, EJ Marchiori US Patent 10,673,720, 2020 | 7 | 2020 |
| Peptide classification using optimal and information theoretic syntactic modeling E Aygün, BJ Oommen, Z Cataltepe Pattern Recognition 43 (11), 3891-3899, 2010 | 4 | 2010 |
| Protein Function Prediction with Amino Acid Sequence and Secondary Structure Alignment Scores E Aygün, C Kömürlü, Z Aydin, Z Çataltepe HIBIT 2008, 18-20, 2008 | 4 | 2008 |
| Importance of secondary structure elements for prediction of GO annotations A Filiz, E Aygün, Ö Keskin, Z Cataltepe Hibit2008, 2008 | 4 | 2008 |
| On utilizing optimal and information theoretic syntactic modeling for peptide classification E Aygün, BJ Oommen, Z Cataltepe IAPR International Conference on Pattern Recognition in Bioinformatics, 24-35, 2009 | 3 | 2009 |
| The history of philosophy DC Önduygu, H Kuşçu, E Aygün https://www.denizcemonduygu.com/portfolio/the-history-of-philosophy/, 2014 | 2* | 2014 |
| Dimensionality Reduction for Protein Function Prediction Z Cataltepe, E Aygun, A Filiz, O Keskin, C Komurlu, Y Altunbasak Automated Function Prediction (AFP)/Biosapiens Joint Special Interest Group …, 2007 | 2 | 2007 |
| A formal treatment of generalized preferential attachment and its empirical validation. CoRR, abs A Herdagdelen, E Aygun, H Bingol arXiv preprint nlin/0609042, 2006 | 2 | 2006 |
| Measuring Preferential Attachment in a Hyper-Textual Dictionary Reference Network: Eksi Sözlük A Herdagdelen, E Aygun, H Bingol Boğaziçi University, 0 | 1 | |
| Learning to cooperate: Emergent communication in multi-agent navigation E Aygun, D Precup Proceedings of the Annual Meeting of the Cognitive Science Society 42, 2020 | | 2020 |
Doina PrecupDeepMind and McGill University在 cs.mcgill.ca 的電子郵件地址已通過驗證
