Zheda Mai

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 6 papers; trusts 583 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 225 citations into it; #10,619 of 35,345 by trust here, #7,010 by citations
• Computer Vision and Pattern Recognition — 196 citations into it; #16,003 of 21,575 by trust here, #6,606 by citations
• Meta & Continual Learning — 150 citations into it; #364 of 1,041 by trust here, #166 by citations
• Representation & Self-Supervised Learning — 93 citations into it
• Optimization & Training — 26 citations into it
• Reinforcement Learning — 23 citations into it
• Radiology, Nuclear Medicine and Imaging — 19 citations into it
• Evaluation & Benchmarks — 17 citations into it

Whom Zheda Mai trusts overall

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

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

Who trusts Zheda Mai overall

1. Hongwei Yan
2. Yiduo Guo
3. Da-Wei Zhou
4. Yaqian Zhang
5. Gobinda Saha
6. Yanan Gu
7. Yujie Wei
8. Liyuan Wang
9. Zhen Wang
10. Zifeng Wang

Papers from Zheda Mai's perspective

Ordered by how strongly the researchers Zheda Mai 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. 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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Online Continual Learning in Image Classification: An Empirical Survey (2021) — 526 citations
• Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning (2021) — 237 citations
• CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions (2020) — 54 citations
• Batch-level Experience Replay with Review for Continual Learning (2020) — 18 citations
• 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