Viveka Kulharia

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 99 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it; #20,718 of 21,575 by trust here, #9,722 by citations
• Artificial Intelligence — 31 citations into it
• Generative Models — 20 citations into it; #1,880 of 1,956 by trust here, #1,110 by citations
• Natural Language Processing — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Viveka Kulharia trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Richard Socher
6. Diederik P. Kingma
7. Jia Deng
8. Yann LeCun
9. Ross B. Girshick
10. Ilya Sutskever

Who trusts Viveka Kulharia overall

1. Ngoc-Trung Tran
2. Animesh Karnewar
3. Garrett Wilson
4. Divya Saxena
5. Yongjun Hong
6. Ke Li
7. Abdul Jabbar
8. Ting-Chun Wang
9. Ze Wang
10. Chaoyue Wang

Papers from Viveka Kulharia's perspective

Ordered by how strongly the researchers Viveka Kulharia trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multi-agent Diverse Generative Adversarial Networks (2017) — 332 citations
• Calibrating Deep Neural Networks using Focal Loss (2020) — 646 citations