Jongjin Park
Computer Vision and Pattern Recognition · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 185 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 38 citations into it
- Artificial Intelligence — 30 citations into it
- Optimization & Training — 11 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Model Architectures — 9 citations into it
- Signal Processing — 7 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Efficiency & Compression — 5 citations into it
Whom Jongjin Park trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Christian Szegedy
- Yann LeCun
- Yoshua Bengio
- Sergey Ioffe
- Ross B. Girshick
- Ilya Sutskever
- Diederik P. Kingma
Who trusts Jongjin Park overall
Papers from Jongjin Park's perspective
Ordered by how strongly the researchers Jongjin Park 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)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Regularizing Class-Wise Predictions via Self-Knowledge Distillation (2020) — 350 citations
- Regularizing Predictions via Class-wise Self-knowledge Distillation (2019) — 3 citations