Amos Gropp

Computational Mechanics · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computational Mechanics — 26 citations into it; #7,339 of 10,001 by trust here, #3,652 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #15,949 of 21,575 by trust here, #11,721 by citations
• Computer Graphics and Computer-Aided Design — 16 citations into it
• 3D Vision & Pose — 15 citations into it
• Artificial Intelligence — 6 citations into it

Whom Amos Gropp trusts overall

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

1. Stanley J. Osher
2. Diederik P. Kingma
3. Hongkai Zhao
4. Gerald Teschl
5. Zhiqin Chen
6. Behnam Neyshabur
7. William E. Lorensen
8. Jimmy Ba
9. Geoffrey E. Hinton
10. Alex Krizhevsky

Who trusts Amos Gropp overall

1. Songyou Peng
2. Lior Yariv
3. Vincent Sitzmann
4. Michael Oechsle
5. Qiancheng Fu
6. Bowen Wen
7. N. Rozen
8. Zehao Yu
9. Kai Zhang
10. Hsueh-Ti Derek Liu

Papers from Amos Gropp's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. GENERATIVE ADVERSARIAL NETS
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Implicit Geometric Regularization for Learning Shapes (2020) — 1,034 citations