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I. Oseledets

79 papers hereh-index 13710 citations130 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author29
  • last author48

Across the 77 of 79 papers where every author was matched, so the position is known.

fields
  • cs.LG26
  • cs.CV15
  • cs.CL12
  • cs.AI6
  • cs.NE3
  • math.NA3
same name
  • I. Oseledets — 4 papers, h 51

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

works on
coefficient decay scaling 1high-dimensional pdes 1neural network approximation 1physics-informed neural networks 1spectral methods 1

From the 1 of 79 linked papers with an AI index.

activity
20242026
most citedAstral: training physics-informed neural networks with error majorants

1 citations · 1 across the 29 of their papers we have counts for

collaborators
Showing math.NAShow all

3 papers · 1 filter

math.NA2026

Spectral-Informed Neural Networks Outperform Spectral Methods in High-dimensional PDEs

Tianchi Yu, Ivan Oseledets

The paper introduces Modified Spectral-Informed Neural Networks (SINNs) that combine spectral methods with physics-informed neural networks, using coefficient decay scaling and bas…

math.NA2026

Locally Subspace-Informed Neural Operators for Efficient Multiscale PDE Solving

Alexander Rudikov, Vladimir Fanaskov, Sergei Stepanov +4

Neural operators (NOs) struggle with high-contrast multiscale partial differential equations (PDEs), where fine-scale heterogeneities cause large errors. To address this, we use th…

math.NA2025

Spectral Analysis of the Weighted Frobenius Objective

Vladislav Trifonov, Ivan Oseledets, Ekaterina Muravleva

We analyze a weighted Frobenius loss for approximating symmetric positive definite matrices in the context of preconditioning iterative solvers. Unlike the standard Frobenius norm,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.