Yingjun Du

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 9 citations into it

Whom Yingjun Du trusts overall

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

1. Alex Krizhevsky
2. J. Urgen Schmidhuber
3. Alex Graves
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Yoshua Bengio
7. Ruslan Salakhutdinov
8. Chelsea Finn
9. Yann LeCun
10. Radford M. Neal

Papers from Yingjun Du's perspective

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

Their papers

• Learning to Learn Kernels with Variational Random Features (2020) — 38 citations