Ning Chen

Artificial Intelligence · with Lv · 2021

A researcher in the Science corpus: 1 paper; trusts 186 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 41 citations into it
• Model Architectures — 18 citations into it
• Optimization & Training — 13 citations into it
• Information Systems — 6 citations into it
• Molecular Biology — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Ning Chen trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Yoav Freund
5. Kaiming He
6. Leo Breiman
7. Alex Krizhevsky
8. Robert E. Schapire
9. Jerome H. Friedman
10. Christian Szegedy

Papers from Ning Chen's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A Survey on ensemble learning under the era of deep learning (2021) — 358 citations