Robert Schaback

Computational Mechanics · 2000–2015

A researcher in the Science corpus: 9 papers; trusts 29 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 38 citations into it; #1,336 of 10,001 by trust here, #2,782 by citations
• Mechanics of Materials — 34 citations into it; #563 of 6,291 by trust here, #1,205 by citations
• Electrical and Electronic Engineering — 11 citations into it
• Mathematical Physics — 9 citations into it
• Statistical Learning Theory — 8 citations into it
• Applied Mathematics — 5 citations into it
• Artificial Intelligence — 5 citations into it
• Civil and Structural Engineering — 5 citations into it; #3,865 of 6,160 by trust here, #2,794 by citations

Whom Robert Schaback trusts overall

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

1. Charles A. Micchelli
2. Tobin A. Driscoll
3. Bengt Fornberg
4. Yiu Chung Benny Hon
5. James Stewart
6. Francis J. Narcowich
7. Satya N. Atluri
8. Grace Wahba
9. Bernhard Schölkopf
10. John Shawe-Taylor

Who trusts Robert Schaback overall

1. Bengt Fornberg
2. Natasha Flyer
3. Guirong Liu
4. Gregory E. Fasshauer
5. Shengyin Wang
6. Yuantong T. Gu
7. Chris J. Oates
8. Michael Y. Wang
9. Elisabeth Larsson
10. Jack G. Zhang

Papers from Robert Schaback's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Interpolation of scattered data: Distance matrices and conditionally positive definite functions
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Interpolation with variably scaled kernels (2015) — 47 citations
• Approximation of eigenfunctions in kernel-based spaces (2014) — 64 citations
• Limit problems for interpolation by analytic radial basis functions (2008) — 60 citations
• Results on meshless collocation techniques (2006) — 170 citations
• Kernel techniques: From machine learning to meshless methods (2006) — 347 citations
• Multivariate Interpolation by Polynomials and Radial Basis Functions (2005) — 167 citations
• Reconstruction of Multivariate Functions from Scattered Data (2003) — 60 citations
• Characterization and construction of radial basis functions (2001) — 147 citations
• A unified theory of radial basis functions Native Hilbert spaces for radial basis functions II (2000) — 79 citations