Karel Matous

Mechanics of Materials · 2008–2017

A researcher in the Science corpus: 4 papers; trusts 26 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Mechanics of Materials — 83 citations into it; #5,262 of 6,291 by trust here, #4,595 by citations
• Computational Theory and Mathematics — 46 citations into it; #10,746 of 12,182 by trust here, #9,804 by citations
• Materials Chemistry — 20 citations into it
• Biomedical Engineering — 18 citations into it
• Computational Mechanics — 16 citations into it
• Mechanical Engineering — 13 citations into it
• Electrical and Electronic Engineering — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Karel Matous trusts overall

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

1. C. Miehé
2. Pedro Ponte Castañeda
3. V. Kouznetsova
4. M. Finnis
5. W. Brekelmans
6. Josh Tenenbaum
7. Mgd Marc Geers
8. Vin de Silva
9. Shaker A. Meguid
10. Michael A. Groeber

Who trusts Karel Matous overall

1. Qizhi He
2. M. Kulkarni
3. F. Otero
4. Clemens V. Verhoosel
5. Mgd Marc Geers
6. Jiun-Shyan Chen
7. Vinh Phu Nguyen
8. V. Kouznetsova
9. X. Martínez
10. Joris J. C. Remmers

Papers from Karel Matous's perspective

Ordered by how strongly the researchers Karel Matous 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials (2017) — 480 citations
• An adaptive spacetime discontinuous Galerkin method for cohesive models of elastodynamic fracture (2010) — 56 citations
• Coupled multi‐scale cohesive modeling of failure in heterogeneous adhesives (2010) — 63 citations
• Multiscale cohesive failure modeling of heterogeneous adhesives (2008) — 168 citations