| Classifying phenotypes based on the community structure of human brain networks A Kurmukov, M Ananyeva, Y Dodonova, B Gutman, J Faskowitz, ... Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging …, 2017 | 12 | 2017 |
| Time-Dependent Next-Basket Recommendations S Naumov, M Ananyeva, O Lashinin, S Kolesnikov, DI Ignatov Advances in Information Retrieval: 45th European Conference on Information …, 2023 | 4 | 2023 |
| GSM: Inductive Learning on Dynamic Graph Embeddings M Ananyeva, I Makarov, M Pendiukhov International Conference on Network Analysis, 85-99, 2018 | 3 | 2018 |
| Information propagation strategies in online social networks R Laptsuev, M Ananyeva, D Meinster, I Karpov, I Makarov, LE Zhukov International Conference on Network Analysis, 319-328, 2016 | 3 | 2016 |
| Towards interaction-based user embeddings in sequential recommender models M Ananyeva, O Lashinin, V Ivanova, S Kolesnikov, DI Ignatov | 2 | 2022 |
| RecBaselines2023: a new dataset for choosing baselines for recommender models V Ivanova, O Lashinin, M Ananyeva, S Kolesnikov arXiv preprint arXiv:2306.14292, 2023 | 1 | 2023 |
| Make your next item recommendation model time sensitive E Makhneva, A Sverkunova, O Lashinin, M Ananyeva, S Kolesnikov Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation …, 2023 | 1 | 2023 |
| Next-Basket Recommendation Constrained by Total Cost O Lashinin, M Ananyeva | 1 | 2022 |
| Time-Aware Item Weighting for the Next Basket Recommendations A Romanov, O Lashinin, M Ananyeva, S Kolesnikov Proceedings of the 17th ACM Conference on Recommender Systems, 985-992, 2023 | | 2023 |
| Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations D Krasilnikov, O Lashinin, M Tsygankov, M Ananyeva, S Kolesnikov | | 2023 |
| Revisiting the performance evaluation of knowledge-aware recommender systems: are we making progress? M Ananyeva, O Lashinin, M Kuznetsova | | 2022 |
Oleg LashininTinkoffVerified email at phystech.edu
