Karan Grewal

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 141 researchers and is trusted by 517 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 42 citations into it; #1,873 of 21,575 by trust here, #2,637 by citations
• Artificial Intelligence — 37 citations into it; #6,865 of 35,345 by trust here, #3,487 by citations
• Representation & Self-Supervised Learning — 33 citations into it; #1,166 of 3,145 by trust here, #478 by citations
• Generative Models — 21 citations into it
• Signal Processing — 7 citations into it
• Neuroscience — 5 citations into it

Whom Karan Grewal trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Kaiming He
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Sergey Ioffe
10. Christian Szegedy

Who trusts Karan Grewal overall

1. Xinlei Chen
2. Jiaming Song
3. Yonglong Tian
4. Kaiming He
5. Yoshua Bengio
6. Ishan Misra
7. Stefano Ermon
8. Phillip Isola
9. Chen Sun
10. Sindy Löwe

Papers from Karan Grewal's perspective

Ordered by how strongly the researchers Karan Grewal 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Learning deep representations by mutual information estimation and maximization (2018) — 3,036 citations