Dongsub Shim

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 2 papers; trusts 81 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it
• Artificial Intelligence — 46 citations into it; #31,657 of 35,345 by trust here, #15,542 by citations
• Representation & Self-Supervised Learning — 31 citations into it
• Meta & Continual Learning — 27 citations into it; #962 of 1,041 by trust here, #568 by citations
• Reinforcement Learning — 10 citations into it
• Optimization & Training — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Dongsub Shim trusts overall

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

1. Alex Krizhevsky
2. Arslan Chaudhry
3. Rahaf Aljundi
4. Geoffrey E. Hinton
5. Marc'Aurelio Ranzato
6. Oriol Vinyals
7. Yoshua Bengio
8. Yann LeCun
9. Diederik P. Kingma
10. Kaiming He

Who trusts Dongsub Shim overall

1. Yiduo Guo
2. Lucas Caccia
3. Jiangpeng He
4. Gobinda Saha
5. Zheda Mai
6. Julien Pourcel
7. Hongwei Yan
8. Yanan Gu
9. Lilly Kumari
10. Zhen Wang

Papers from Dongsub Shim's perspective

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

Their papers

• Online Class-Incremental Continual Learning with Adversarial Shapley Value (2020) — 267 citations
• Adversarial Shapley Value Experience Replay for Task-Free Continual Learning (2020) — 6 citations