Ayan Chakrabarti

Computer Vision and Pattern Recognition · 2010–2021

A researcher in the Science corpus: 7 papers; trusts 680 researchers and is trusted by 116 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 109 citations into it; #2,904 of 21,575 by trust here, #5,711 by citations
• Artificial Intelligence — 46 citations into it
• Media Technology — 32 citations into it; #161 of 3,621 by trust here, #941 by citations
• Model Architectures — 22 citations into it
• Generative Models — 14 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Computational Mechanics — 8 citations into it
• Optimization & Training — 8 citations into it

Whom Ayan Chakrabarti trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Yair Weiss
4. Alex Krizhevsky
5. Anat Levin
6. Kaiming He
7. Diederik P. Kingma
8. Li Xu
9. Rob Fergus
10. Yoshua Bengio

Who trusts Ayan Chakrabarti overall

1. Yongqiang Zhang
2. Yancheng Bai
3. Kaihao Zhang
4. Seungjun Nah
5. Boyu Lu
6. Igor Vasiljevic
7. Orest Kupyn
8. Dongwei Ren
9. Boaz Arad
10. Vivek Sharma

Papers from Ayan Chakrabarti's perspective

Ordered by how strongly the researchers Ayan Chakrabarti 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• A Neural Approach to Blind Motion Deblurring (2016) — 472 citations
• Examining the Impact of Blur on Recognition by Convolutional Networks (2016) — 213 citations
• Analyzing spatially-varying blur (2010) — 218 citations
• Understanding Robustness of Transformers for Image Classification (2021) — 515 citations
• Stabilizing GAN Training with Multiple Random Projections (2017) — 85 citations
• Color Constancy by Learning to Predict Chromaticity from Luminance (2015) — 38 citations
• Statistics of real-world hyperspectral images (2011) — 613 citations