| RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback I Shenbin, A Alekseev, E Tutubalina, V Malykh, SI Nikolenko Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 205 | 2020 |
| nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset K Khrabrov, I Shenbin, A Ryabov, A Tsypin, A Telepov, A Alekseev, ... Physical Chemistry Chemical Physics 24 (42), 25853-25863, 2022 | 20 | 2022 |
| AspeRa: Aspect-based Rating Prediction Model SI Nikolenko, E Tutubalina, V Malykh, I Shenbin, A Alekseev Advances in Information Retrieval: 41st European Conference on IR Research …, 2019 | 15* | 2019 |
| DetIE: Multilingual Open Information Extraction Inspired by Object Detection M Vasilkovsky, A Alekseev, V Malykh, I Shenbin, E Tutubalina, D Salikhov, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (10), 11412 …, 2022 | 14 | 2022 |
| Neural Click Models for Recommender Systems M Shirokikh, I Shenbin, A Alekseev, A Volodkevich, A Vasilev, ... Proceedings of the 47th International ACM SIGIR Conference on Research and …, 2024 | | 2024 |
| ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering I Shenbin, S Nikolenko The Twelfth International Conference on Learning Representations, 2024 | | 2024 |
| Machine Learning for SAT: Restricted Heuristics and New Graph Representations M Shirokikh, I Shenbin, A Alekseev, S Nikolenko arXiv preprint arXiv:2307.09141, 2023 | | 2023 |
| Learning word embeddings from characters I Shenbin Saint Petersburg State University, 2017 | | 2017 |
