Peter D. Chang

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 7 citations into it

Whom Peter D. Chang trusts overall

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

1. Yann LeCun
2. Kaiming He
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Christian Szegedy
7. Alex Krizhevsky
8. Matthew D. Zeiler
9. Sergey Ioffe
10. Yurii E. Nesterov

Who trusts Peter D. Chang overall

1. Lauv Patel

Papers from Peter D. Chang's perspective

Ordered by how strongly the researchers Peter D. Chang 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. Attention is All you Need (Neural Information Processing Systems)
7. Going deeper with convolutions
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas (2018) — 382 citations
• MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling (2018) — 81 citations