André Uschmajew

Computational Mathematics · 2011–2020

A researcher in the Science corpus: 10 papers; trusts 94 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Computational Mathematics — 142 citations into it; #56 of 612 by trust here, #112 by citations
• Computational Theory and Mathematics — 121 citations into it; #1,199 of 12,182 by trust here, #2,565 by citations
• Computational Mechanics — 72 citations into it; #1,165 of 10,001 by trust here, #2,361 by citations
• Atomic and Molecular Physics, and Optics — 43 citations into it; #6,995 of 7,135 by trust here, #5,903 by citations
• Statistical and Nonlinear Physics — 42 citations into it
• Artificial Intelligence — 40 citations into it
• Numerical Analysis — 37 citations into it
• Numerical Methods & Scientific Computing — 37 citations into it

Whom André Uschmajew trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Ivan V. Oseledets
2. Tamara G. Kolda
3. Christian Lubich
4. Lars Grasedyck
5. Wolfgang Hackbusch
6. Daniel Kressner
7. Bart Vandereycken
8. Boris N. Khoromskij
9. Brett W. Bader
10. Sebastian Holtz

Who trusts André Uschmajew overall

1. Thorsten Rohwedder
2. Qingyun Wu
3. Andrzej S. Cichocki
4. Anh Huy Phan
5. Daniel Kressner
6. Bart Vandereycken
7. Reinhold Schneider
8. Andreas Arnold
9. Hongning Wang
10. Lars Grasedyck

Papers from André Uschmajew's perspective

Ordered by how strongly the researchers André Uschmajew trusts endorse each paper. Same corpus, a different order for every researcher.

1. Tensor Decompositions and Applications
2. f¨ur Mathematik in den Naturwissenschaften Leipzig Hierarchical Singular Value Decomposition of Tensors
3. Some mathematical notes on three-mode factor analysis
4. A Multilinear Singular Value Decomposition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. A New Scheme for the Tensor Representation
7. ImageNet classification with deep convolutional neural networks
8. Matrix Computations
9. Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem
10. Gradient-based learning applied to document recognition

Their papers

• Local Convergence of the Alternating Least Squares Algorithm for Canonical Tensor Approximation (2012) — 222 citations
• The geometry of algorithms using hierarchical tensors (2013) — 139 citations
• On Local Convergence of Alternating Schemes for Optimization of Convex Problems in the Tensor Train Format (2013) — 116 citations
• Geometric Methods on Low-Rank Matrix and Tensor Manifolds (2020) — 52 citations
• On critical points of quadratic low-rank matrix optimization problems (2020) — 20 citations
• Approximation rates for the hierarchical tensor format in periodic Sobolev spaces (2014) — 82 citations
• Zur Theorie der Niedrigrangapproximation in Tensorprodukten von Hilberträumen (2013)
• Bridging the gap between quantum Monte Carlo and F12-methods (2012) — 9 citations
• Regularity of Tensor Product Approximations to Square Integrable Functions (2011) — 14 citations
• LOCAL CONVERGENCE OF ALTERNATING SCHEMES FOR OPTIMIZATION OF CONVEX PROBLEMS IN THE TT FORMAT (2011)