Per-Gunnar Martinsson
Computational Mechanics · 2003–2020
A researcher in the Science corpus: 9 papers; trusts 74 researchers and is trusted by 105 researchers here, as inferred from the citation graph.
Subfields
- Computational Mechanics — 54 citations into it; #343 of 10,001 by trust here, #403 by citations
- Artificial Intelligence — 49 citations into it; #3,232 of 35,345 by trust here, #6,064 by citations
- Statistics and Probability — 44 citations into it; #6,638 of 12,932 by trust here, #5,661 by citations
- Computational Theory and Mathematics — 41 citations into it; #5,781 of 12,182 by trust here, #6,798 by citations
- Computer Vision and Pattern Recognition — 21 citations into it; #12,595 of 21,575 by trust here, #9,872 by citations
- Statistical Learning Theory — 20 citations into it
- Computational Mathematics — 19 citations into it; #23 of 612 by trust here, #20 by citations
- Applied Mathematics — 17 citations into it
Whom Per-Gunnar Martinsson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Joel A. Tropp
- Francis R. Bach
- Michael W. Mahoney
- Tamás Sarlós
- Roberto Imbuzeiro Oliveira
- Gene H. Golub
- Ali Rahimi
- Nir Ailon
- L. Eon Bottou
- Petros Drineas
Who trusts Per-Gunnar Martinsson overall
- Joel A. Tropp
- David J. Biagioni
- Ronald R. Coifman
- N. Benjamin Erichson
- George C. Linderman
- Steven L. Brunton
- Vladimir Rokhlin
- Nathan Halko
- Alex Gittens
- David P. Woodruff
Papers from Per-Gunnar Martinsson's perspective
Ordered by how strongly the researchers Per-Gunnar Martinsson trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions (2009) — 3,165 citations
- Randomized numerical linear algebra: Foundations and algorithms (2020) — 522 citations
- A randomized algorithm for the decomposition of matrices (2011) — 370 citations
- A fast direct solver for boundary integral equations in two dimensions (2003) — 358 citations
- On the Compression of Low Rank Matrices (2005) — 370 citations
- VIBRATIONS OF LATTICE STRUCTURES AND PHONONIC BAND GAPS (2003) — 251 citations
- An Algorithm for the Principal Component Analysis of Large Data Sets (2010) — 308 citations
- Randomized algorithms for the low-rank approximation of matrices (2007) — 596 citations
- A fast algorithm for the inversion of general Toeplitz matrices (2004) — 88 citations