Zixuan Ke

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 11 papers; trusts 1,042 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 493 citations into it; #5,163 of 35,345 by trust here, #7,657 by citations
• Computer Vision and Pattern Recognition — 286 citations into it; #5,784 of 21,575 by trust here, #6,873 by citations
• Meta & Continual Learning — 269 citations into it; #172 of 1,041 by trust here, #231 by citations
• Representation & Self-Supervised Learning — 129 citations into it; #2,266 of 3,145 by trust here, #2,355 by citations
• Natural Language Processing — 112 citations into it
• Reinforcement Learning — 58 citations into it
• Model Architectures — 45 citations into it
• Large Language Models — 40 citations into it; #405 of 799 by trust here, #634 by citations

Whom Zixuan Ke trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Bing Liu
5. Kaiming He
6. Diederik P. Kingma
7. Yann LeCun
8. Marc'Aurelio Ranzato
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Zixuan Ke overall

1. Gyuhak Kim
2. Bing Liu
3. Bin Liu
4. Jorge Armando Mendez Mendez
5. B. Ermiş
6. Hu Xu
7. Yiduo Guo
8. Qi Qin
9. Diana Benavides Prado
10. Changnan Xiao

Papers from Zixuan Ke's perspective

Ordered by how strongly the researchers Zixuan Ke 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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

• Open-World Continual Learning: Unifying Novelty Detection and Continual Learning (2023) — 34 citations
• Continual Pre-training of Language Models (2023) — 242 citations
• Continual Learning of Natural Language Processing Tasks: A Survey (2022) — 116 citations
• A Theoretical Study on Solving Continual Learning (2022) — 111 citations
• A Multi-Head Model for Continual Learning via Out-of-Distribution Replay (2022) — 47 citations
• Continual Training of Language Models for Few-Shot Learning (2022) — 45 citations
• Continual Learning with Knowledge Transfer for Sentiment Classification (2021) — 36 citations
• Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning (2021) — 159 citations
• Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks (2021) — 165 citations
• Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks (2021) — 95 citations
• CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks (2021) — 68 citations