Aman Sinha

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 62 researchers and is trusted by 63 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it; #7,317 of 35,345 by trust here, #7,241 by citations
• Safety, Robustness & Interpretability — 40 citations into it; #257 of 2,251 by trust here, #383 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Statistics and Probability — 29 citations into it
• Management Science and Operations Research — 27 citations into it
• Optimization & Training — 19 citations into it; #924 of 2,601 by trust here, #988 by citations
• Statistical Learning Theory — 16 citations into it
• Control and Systems Engineering — 12 citations into it

Whom Aman Sinha trusts overall

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

1. Ian J. Goodfellow
2. Peter L. Bartlett
3. Bastian Goldlücke
4. Geoffrey E. Hinton
5. Ali Rahimi
6. Dimitri P. Bertsekas
7. Jose H. Blanchet
8. Kaiming He
9. Christian Szegedy
10. Stéphane Boucheron

Who trusts Aman Sinha overall

1. John C. Duchi
2. Fanny Yang
3. Eric Wong
4. Weihua Hu
5. Christina Heinze-Deml
6. Simone Scardapane
7. Yang Song
8. David Stutz
9. Adarsh Subbaswamy
10. Sergey Levine

Papers from Aman Sinha's perspective

Ordered by how strongly the researchers Aman Sinha 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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
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

• Certifying Some Distributional Robustness with Principled Adversarial Training (2017) — 971 citations
• Certifiable Distributional Robustness with Principled Adversarial Training (2017) — 374 citations
• Learning Kernels with Random Features (2016) — 108 citations