Quadrature-based features for kernel approximation M Munkhoeva, Y Kapushev, E Burnaev, I Oseledets Advances in Neural Information Processing Systems, 9147-9156, 2018 | 68 | 2018 |
The Shape of Data: Intrinsic Distance for Data Distributions A Tsitsulin, M Munkhoeva, D Mottin, P Karras, A Bronstein, I Oseledets, ... Iclr 2020: Proceedings of the International Conference on Learning …, 2020 | 54 | 2020 |
FREDE: anytime graph embeddings A Tsitsulin, M Munkhoeva, D Mottin, P Karras, I Oseledets, E Müller Proceedings of the VLDB Endowment 14 (6), 1102-1110, 2021 | 42* | 2021 |
Just slaq when you approximate: Accurate spectral distances for web-scale graphs A Tsitsulin, M Munkhoeva, B Perozzi Proceedings of the Web Conference 2020, 2697-2703, 2020 | 24 | 2020 |
CC-Cert: A probabilistic approach to certify general robustness of neural networks M Pautov, N Tursynbek, M Munkhoeva, N Muravev, A Petiushko, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7975-7983, 2022 | 20 | 2022 |
Grasp: Graph alignment through spectral signatures J Hermanns, A Tsitsulin, M Munkhoeva, A Bronstein, D Mottin, P Karras Web and Big Data: 5th International Joint Conference, APWeb-WAIM 2021 …, 2021 | 11 | 2021 |
GRASP: Scalable Graph Alignment by Spectral Corresponding Functions J Hermanns, K Skitsas, A Tsitsulin, M Munkhoeva, A Kyster, S Nielsen, ... ACM Transactions on Knowledge Discovery from Data 17 (4), 1-26, 2023 | 7 | 2023 |
Unsupervised embedding quality evaluation A Tsitsulin, M Munkhoeva, B Perozzi Topological, Algebraic and Geometric Learning Workshops 2023, 169-188, 2023 | 3 | 2023 |
Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning M Munkhoeva, I Oseledets Advances in Neural Information Processing Systems (NeurIPS 2023), 2023 | 2 | 2023 |
AIRI at RRG24: LLaVa with specialised encoder and decoder M Munkhoeva, D Umerenkov, V Samokhin Proceedings of the 23rd Workshop on Biomedical Natural Language Processing …, 2024 | | 2024 |
FAST NUMERICAL LINEAR ALGEBRA METHODS FOR MACHINE LEARNING M MUNKHOEVA | | |