G. Santhanam

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it; #14,486 of 35,345 by trust here, #32,362 by citations
• Computer Vision and Pattern Recognition — 15 citations into it; #9,362 of 21,575 by trust here, #16,787 by citations
• Safety, Robustness & Interpretability — 14 citations into it
• Optimization & Training — 7 citations into it
• Generative Models — 6 citations into it

Whom G. Santhanam trusts overall

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

1. Ian J. Goodfellow
2. Christian Szegedy
3. Geoffrey E. Hinton
4. Sergey Ioffe
5. Alex Krizhevsky
6. Ning Qian
7. Ilya Sutskever
8. Yoshua Bengio
9. Alec Radford
10. Nicolas Papernot

Who trusts G. Santhanam overall

1. Adnan Siraj Rakin
2. Rushil Anirudh
3. Adnan Qayyum
4. Zhezhi He
5. Junaid Qadir
6. Jayaraman J. Thiagarajan
7. Deliang Fan
8. Muhammad Bilal
9. Bhavya Kailkhura

Papers from G. Santhanam's perspective

Ordered by how strongly the researchers G. Santhanam 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. Long Short-Term Memory
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Defending Against Adversarial Attacks by Leveraging an Entire GAN (2018) — 40 citations
• Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit (2017) — 210 citations