Ping-yeh Chiang

arXiv.org · 2019–2023

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Ping-yeh Chiang trusts overall

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

1. David John Cameron MacKay
2. Geoffrey E. Hinton
3. Hao Li
4. Alec Radford
5. Ian J. Goodfellow
6. Alex Krizhevsky
7. Yoshua Bengio
8. Diederik P. Kingma
9. Yann LeCun
10. Kaiming He

Papers from Ping-yeh Chiang's perspective

Ordered by how strongly the researchers Ping-yeh Chiang 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Distilling the Knowledge in a Neural Network (arXiv.org)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Compressing GANs using Knowledge Distillation (2019) — 87 citations
• Baseline Defenses for Adversarial Attacks Against Aligned Language Models (2023) — 743 citations