David H. Gutman

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 9 citations into it
• Computational Mechanics — 8 citations into it; #6,770 of 10,001 by trust here, #9,862 by citations
• Numerical Analysis — 8 citations into it; #2,389 of 3,586 by trust here, #3,457 by citations
• Artificial Intelligence — 5 citations into it; #24,251 of 35,345 by trust here, #34,943 by citations

Whom David H. Gutman trusts overall

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

1. Martin Jaggi
2. Simon Lacoste-Julien
3. Yurii E. Nesterov
4. Julian Parsert
5. Gábor Braun
6. Amir Beck
7. Cezary Kaliszyk

Who trusts David H. Gutman overall

1. Thomas Kerdreux
2. Lewis Liu
3. Simon Lacoste-Julien

Papers from David H. Gutman's perspective

Ordered by how strongly the researchers David H. Gutman 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. ImageNet: A large-scale hierarchical image database
7. Learning Multiple Layers of Features from Tiny Images
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Long Short-Term Memory

Their papers

• The condition number of a function relative to a set (2019) — 26 citations