Jonghyun Choi
Artificial Intelligence · with Ha · 2019–2022
A researcher in the Science corpus: 4 papers; trusts 401 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 129 citations into it; #13,666 of 35,345 by trust here, #10,207 by citations
- Computer Vision and Pattern Recognition — 93 citations into it; #9,174 of 21,575 by trust here, #7,421 by citations
- Meta & Continual Learning — 49 citations into it; #434 of 1,041 by trust here, #312 by citations
- Optimization & Training — 34 citations into it; #2,132 of 2,601 by trust here, #2,313 by citations
- Representation & Self-Supervised Learning — 34 citations into it
- Reinforcement Learning — 11 citations into it
- Efficiency & Compression — 10 citations into it
- Model Architectures — 10 citations into it
Whom Jonghyun Choi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
- Arslan Chaudhry
- Rahaf Aljundi
- Ross B. Girshick
Who trusts Jonghyun Choi overall
Papers from Jonghyun Choi's perspective
Ordered by how strongly the researchers Jonghyun Choi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Rainbow Memory: Continual Learning with a Memory of Diverse Samples (2021) — 485 citations
- Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference (2021) — 89 citations
- Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries (2022) — 61 citations
- Incremental Learning with Maximum Entropy Regularization: Rethinking Forgetting and Intransigence (2019) — 23 citations