Neela Kaushik

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 180 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 62 citations into it; #12,651 of 21,575 by trust here, #6,795 by citations
• Artificial Intelligence — 32 citations into it; #20,230 of 35,345 by trust here, #9,641 by citations
• Representation & Self-Supervised Learning — 8 citations into it; #2,337 of 3,145 by trust here, #1,430 by citations

Whom Neela Kaushik trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Baochen Sun
4. Yoshua Bengio
5. Ilya Sutskever
6. Kaiming He
7. Ross B. Girshick
8. Yann LeCun
9. Diederik P. Kingma
10. Kate Saenko

Who trusts Neela Kaushik overall

1. Kuniaki Saito
2. Yogesh Kumar Balaji

Papers from Neela Kaushik's perspective

Ordered by how strongly the researchers Neela Kaushik 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet Large Scale Visual Recognition Challenge
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• VisDA: The Visual Domain Adaptation Challenge (2017) — 929 citations
• VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation (2018) — 206 citations