Mark N. Wegman

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 45 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #16,226 of 35,345 by trust here, #23,077 by citations
• Safety, Robustness & Interpretability — 21 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Signal Processing — 5 citations into it

Whom Mark N. Wegman trusts overall

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

1. Nicholas Carlini
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. David A. Wagner
5. Yann LeCun
6. Alex Krizhevsky
7. Christian Szegedy
8. Ian J. Goodfellow
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Mark N. Wegman overall

1. Dinghuai Zhang
2. Tianyuan Zhang
3. Matthew Norton

Papers from Mark N. Wegman's perspective

Ordered by how strongly the researchers Mark N. Wegman 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. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• L2-Nonexpansive Neural Networks (2018) — 75 citations