Pin-Yu Chen

Artificial Intelligence · with Chen · 2022

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Optimization & Training — 12 citations into it

Whom Pin-Yu Chen trusts overall

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

1. Chelsea Finn
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Sergey Ioffe
6. Oriol Vinyals
7. Diederik P. Kingma
8. J. Urgen Schmidhuber
9. Sergey Levine
10. Ilya Sutskever

Papers from Pin-Yu Chen's perspective

Ordered by how strongly the researchers Pin-Yu Chen trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Their papers

• Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning (2022) — 108 citations