Ekaterina A. Muravleva

According to our database, Ekaterina A. Muravleva authored at least 19 papers between 2018 and 2026.

Collaborative distances:

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

2026

Message-Passing GNNs Fail to Approximate Sparse Triangular Factorizations.

Vladislav Trifonov, Ekaterina A. Muravleva, Ivan V. Oseledets

Trans. Mach. Learn. Res., 2026

2025

PERELMAN: Pipeline for scientific literature meta-analysis. Technical report.

Daniil Sherki, Daniil Merkulov, Alexandra Savina, Ekaterina A. Muravleva

CoRR, December, 2025

Deep Learning for Subspace Regression.

Vladimir Fanaskov, Vladislav Trifonov, Alexander Rudikov, Ekaterina A. Muravleva, Ivan V. Oseledets

CoRR, September, 2025

Spectral Analysis of the Weighted Frobenius Objective.

Vladislav Trifonov, Ivan V. Oseledets, Ekaterina A. Muravleva

CoRR, September, 2025

Geological Field Restoration through the Lens of Image Inpainting.

Vladislav Trifonov, Ivan V. Oseledets, Ekaterina A. Muravleva

CoRR, June, 2025

Locally Subspace-Informed Neural Operators for Efficient Multiscale PDE Solving.

Alexander Rudikov, Vladimir Fanaskov, Sergei Stepanov, Buzheng Shan, Ekaterina A. Muravleva, Yalchin Efendiev, Ivan V. Oseledets

CoRR, May, 2025

Combining Flow Matching and Transformers for Efficient Solution of Bayesian Inverse Problems.

Daniil Sherki, Ivan V. Oseledets, Ekaterina A. Muravleva

CoRR, March, 2025

Can message-passing GNN approximate triangular factorizations of sparse matrices?

Vladislav Trifonov, Ekaterina A. Muravleva, Ivan V. Oseledets

CoRR, February, 2025

2024

On the efficient preconditioning of the Stokes equations in tight geometries.

Vladislav Pimanov, Oleg Iliev, Ivan V. Oseledets, Ekaterina A. Muravleva

Numer. Linear Algebra Appl., December, 2024

ConDiff: A Challenging Dataset for Neural Solvers of Partial Differential Equations.

Vladislav Trifonov, Alexander Rudikov, Oleg Iliev, Ivan V. Oseledets, Ekaterina A. Muravleva

CoRR, 2024

Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers.

Vladislav Trifonov, Alexander Rudikov, Oleg Iliev, Ivan V. Oseledets, Ekaterina A. Muravleva

CoRR, 2024

Quantization of Large Language Models with an Overdetermined Basis.

Daniil Merkulov, Daria Cherniuk, Alexander Rudikov, Ivan V. Oseledets, Ekaterina A. Muravleva, Aleksandr Mikhalev, Boris Kashin

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving.

Alexander Rudikov, Vladimir Fanaskov, Ekaterina A. Muravleva, Yuri M. Laevsky, Ivan V. Oseledets

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

On the structure of the Schur complement matrix for the Stokes equation.

Vladislav Pimanov, Ekaterina A. Muravleva, Ivan V. Oseledets, Oleg Iliev

CoRR, 2023

2022

On a workflow for efficient computation of the permeability of tight sandstones.

Vladislav Pimanov, Vladislav Lukoshkin, Pavel Toktaliev, Oleg Iliev, Ekaterina A. Muravleva, Denis M. Orlov, Vladislav Krutko, Alexander Avdonin, Konrad Steiner, Dmitry A. Koroteev

CoRR, 2022

2019

Microstructure synthesis using style-based generative adversarial network.

Daria Fokina, Ekaterina A. Muravleva, George V. Ovchinnikov, Ivan V. Oseledets

CoRR, 2019

Reconstruction of 3D Porous Media From 2D Slices.

Denis Volkhonskiy, Ekaterina A. Muravleva, Oleg Sudakov, Denis M. Orlov, Boris Belozerov, Evgeny Burnaev, Dmitry A. Koroteev

CoRR, 2019

Approximate Solution of Linear Systems with Laplace-like Operators via Cross Approximation in the Frequency Domain.

Ekaterina A. Muravleva, Ivan V. Oseledets

Comput. Methods Appl. Math., 2019

2018

Data-driven model for the identification of the rock type at a drilling bit.

Nikita Klyuchnikov, Alexey Zaytsev, Arseniy Gruzdev, Georgiy Ovchinnikov, Ksenia Antipova, Leyla S. Ismailova, Ekaterina A. Muravleva, Evgeny Burnaev, Artyom Semenikhin, Alexey Cherepanov, Vitaliy Koryabkin, Igor Simon, Alexey Tsurgan, Fedor Krasnov, Dmitry A. Koroteev

CoRR, 2018