Atul Kumar

Artificial Intelligence · with Mehta · 2017

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it
• Safety, Robustness & Interpretability — 7 citations into it

Whom Atul Kumar trusts overall

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

1. Geoffrey E. Hinton
2. Ian J. Goodfellow
3. Florian Tramèr
4. Nicolas Papernot
5. Oriol Vinyals
6. Christian Szegedy
7. Jonathon Shlens
8. Alex Krizhevsky
9. Yoshua Bengio
10. Yann LeCun

Papers from Atul Kumar's perspective

Ordered by how strongly the researchers Atul Kumar 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. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Distilling the Knowledge in a Neural Network (arXiv.org)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• An Introduction to Adversarial Machine Learning (2017) — 12 citations