815 citations · 3.2k across the 142 of their papers we have counts for
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Robust topology optimization using a posteriori error estimator for the finite element method
Vladislav Pimanov, Ivan Oseledets
In our work, we consider the classical density-based approach to the topology optimization. We propose to modify the discretized cost functional using a posteriori error estimator…
Deep Multigrid: learning prolongation and restriction matrices
Alexandr Katrutsa, Talgat Daulbaev, Ivan Oseledets
This paper proposes the method to optimize restriction and prolongation operators in the two-grid method. The proposed method is straightforwardly extended to the geometric multigr…
Expressive power of recurrent neural networks
Valentin Khrulkov, Alexander Novikov, Ivan Oseledets
Deep neural networks are surprisingly efficient at solving practical tasks, but the theory behind this phenomenon is only starting to catch up with the practice. Numerous works sho…
Neural networks for topology optimization
Ivan Sosnovik, Ivan Oseledets
In this research, we propose a deep learning based approach for speeding up the topology optimization methods. The problem we seek to solve is the layout problem. The main novelty…
AA-ICP: Iterative Closest Point with Anderson Acceleration
A. L. Pavlov, G. V. Ovchinnikov, D. Yu. Derbyshev +2
Iterative Closest Point (ICP) is a widely used method for performing scan-matching and registration. Being simple and robust method, it is still computationally expensive and may b…
Alternating least squares as moving subspace correction
Ivan Oseledets, Maxim Rakhuba, André Uschmajew
In this note we take a new look at the local convergence of alternating optimization methods for low-rank matrices and tensors. Our abstract interpretation as sequential optimizati…