Sangdon Park
Artificial Intelligence · 2017–2020
A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 28 citations into it
- Computer Vision and Pattern Recognition — 13 citations into it
- Safety, Robustness & Interpretability — 10 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Computer Networks and Communications — 7 citations into it
- Statistical Learning Theory — 7 citations into it
- Statistics and Probability — 7 citations into it
- Control and Systems Engineering — 6 citations into it
Whom Sangdon Park trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Bianca Zadrozny
- Kaiming He
- Christian Szegedy
- Ian J. Goodfellow
- Alex Krizhevsky
- Ilya Sutskever
- Yoshua Bengio
- Peter L. Bartlett
- Yann LeCun
Who trusts Sangdon Park overall
Papers from Sangdon Park's perspective
Ordered by how strongly the researchers Sangdon 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- PAC Confidence Predictions for Deep Neural Network Classifiers (2020) — 27 citations
- Resilient Linear Classification: An Approach to Deal with Attacks on Training Data (2017) — 8 citations