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Marina Munkhoeva
Marina Munkhoeva
Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Title
Cited by
Cited by
Year
Quadrature-based features for kernel approximation
M Munkhoeva, Y Kapushev, E Burnaev, I Oseledets
Advances in Neural Information Processing Systems, 9147-9156, 2018
582018
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
412020
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
34*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
212020
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
172022
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
72021
Unsupervised embedding quality evaluation
A Tsitsulin, M Munkhoeva, B Perozzi
Topological, Algebraic and Geometric Learning Workshops 2023, 169-188, 2023
22023
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
12023
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
12023
FAST NUMERICAL LINEAR ALGEBRA METHODS FOR MACHINE LEARNING
M MUNKHOEVA
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Articles 1–10