Marina Munkhoeva

According to our database, Marina Munkhoeva authored at least 15 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Screener: Self-supervised Pathology Segmentation Model for 3D Medical Images.

Mikhail Goncharov, Eugenia Soboleva, Maria Donskova, Ivan V. Oseledets, Marina Munkhoeva, Maxim Panov

CoRR, February, 2025

2024

Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax.

Ivan Butakov, Alexander Sememenko, Aleksander Tolmachev, Andrey Gladkov, Marina Munkhoeva, Alexey A. Frolov

CoRR, 2024

AIRI at RRG24: LLaVa with specialised encoder and decoder.

Marina Munkhoeva, Dmitry Umerenkov, Valentin Samokhin

Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, 2024

2023

GRASP: Scalable Graph Alignment by Spectral Corresponding Functions.

Judith Hermanns, Konstantinos Skitsas, Anton Tsitsulin, Marina Munkhoeva, Alexander Frederiksen Kyster, Simon Nielsen, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras

ACM Trans. Knowl. Discov. Data, May, 2023

Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning.

Marina Munkhoeva, Ivan V. Oseledets

CoRR, 2023

Unsupervised Embedding Quality Evaluation.

Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi

Proceedings of the Topological, 2023

Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning.

Marina Munkhoeva, Ivan V. Oseledets

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

CC-CERT: A Probabilistic Approach to Certify General Robustness of Neural Networks.

Mikhail Pautov, Nurislam Tursynbek, Marina Munkhoeva, Nikita Muravev, Aleksandr Petiushko, Ivan V. Oseledets

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

FREDE: Anytime Graph Embeddings.

Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller

Proc. VLDB Endow., 2021

GRASP: Graph Alignment Through Spectral Signatures.

Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras

Proceedings of the Web and Big Data - 5th International Joint Conference, 2021

2020

FREDE: Linear-Space Anytime Graph Embeddings.

Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller

CoRR, 2020

Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs.

Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

The Shape of Data: Intrinsic Distance for Data Distributions.

Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Intrinsic Multi-scale Evaluation of Generative Models.

Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller

CoRR, 2019

2018

Quadrature-based features for kernel approximation.

Marina Munkhoeva, Yermek Kapushev, Evgeny Burnaev, Ivan V. Oseledets

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018