815 citations · 3.2k across the 142 of their papers we have counts for
160 papers
Sinc Kolmogorov-Arnold network and its application for solving PDEs with singularities
Tianchi Yu, Jingwei Qiu, Jiang Yang +1
In this paper, we propose to use Sinc interpolation in the context of Kolmogorov-Arnold Networks, neural networks with learnable activation functions, which recently gained attenti…
Dynamic Collaborative Filtering for Matrix- and Tensor-based Recommender Systems
Albert Saiapin, Ivan Oseledets, Evgeny Frolov
In production applications of recommender systems, a continuous data flow is employed to update models in real-time. Many recommender models often require complete retraining to ad…
Tensor Train Decomposition for Adversarial Attacks on Computer Vision Models
Andrei Chertkov, Ivan Oseledets
Deep neural networks (DNNs) are widely used today, but they are vulnerable to adversarial attacks. To develop effective methods of defense, it is important to understand the potent…
Another approach to build Lyapunov functions for the first order methods in the quadratic case
Daniil Merkulov, Ivan Oseledets
Lyapunov functions play a fundamental role in analyzing the stability and convergence properties of optimization methods. In this paper, we propose a novel and straightforward appr…
On the structure of the Schur complement matrix for the Stokes equation
Vladislav Pimanov, Ekaterina Muravleva, Ivan Oseledets +1
In this paper, we investigate the structure of the Schur complement matrix for the fully-staggered finite-difference discretization of the stationary Stokes equation. Specifically,…
General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing
Dmitrii Korzh, Mikhail Pautov, Olga Tsymboi +1
Randomized smoothing is the state-of-the-art approach to construct image classifiers that are provably robust against additive adversarial perturbations of bounded magnitude. Howev…