Ian Gemp

Artificial Intelligence · 2014–2016

A researcher in the Science corpus: 2 papers; trusts 44 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it
• Optimization & Training — 31 citations into it
• Reinforcement Learning — 29 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it; #6,129 of 21,575 by trust here, #8,502 by citations
• Generative Models — 17 citations into it; #587 of 1,956 by trust here, #961 by citations
• Computational Mechanics — 14 citations into it
• Computational Theory and Mathematics — 14 citations into it
• Management Science and Operations Research — 12 citations into it

Whom Ian Gemp trusts overall

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

1. Alex Krizhevsky
2. Richard S. Sutton
3. Yann LeCun
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. Ilya Sutskever
9. Kaiming He
10. Tim Salimans

Who trusts Ian Gemp overall

1. Animesh Karnewar
2. Eli Schwartz
3. Garrett Wilson
4. Isabela Albuquerque
5. Dan Zhang
6. Tero Karras
7. Oliver Wang
8. Zizhao Zhang
9. Behnam Neyshabur
10. Gonçalo Mordido

Papers from Ian Gemp's perspective

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

Their papers

• Generative Multi-Adversarial Networks (2016) — 368 citations
• Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces (2014) — 73 citations