Pratik Mazumder

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 550 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 87 citations into it; #14,489 of 35,345 by trust here, #17,776 by citations
• Computer Vision and Pattern Recognition — 81 citations into it; #9,374 of 21,575 by trust here, #11,950 by citations
• Representation & Self-Supervised Learning — 44 citations into it
• Meta & Continual Learning — 40 citations into it; #382 of 1,041 by trust here, #470 by citations
• Radiology, Nuclear Medicine and Imaging — 11 citations into it; #800 of 3,265 by trust here, #1,699 by citations
• Reinforcement Learning — 11 citations into it
• Generative Models — 8 citations into it
• Model Architectures — 8 citations into it

Whom Pratik Mazumder 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. Yann LeCun
6. Diederik P. Kingma
7. Ross B. Girshick
8. Oriol Vinyals
9. Ilya Sutskever
10. Jia Deng

Who trusts Pratik Mazumder overall

1. Da-Wei Zhou
2. Jaya Kalla
3. Keon-Hee Park
4. Han-Jia Ye
5. Do-Yeon Kim
6. Aishwarya Agarwal
7. Haeyong Kang
8. Guangyuan Shi
9. Prashant Bhat
10. Song Tian

Papers from Pratik Mazumder's perspective

Ordered by how strongly the researchers Pratik Mazumder 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Few-Shot Lifelong Learning (2021) — 159 citations
• Rectification-based Knowledge Retention for Continual Learning (2021) — 51 citations
• Calibrating CNNs for Lifelong Learning (2020) — 78 citations