Binxin Ru

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Neural Architecture Search & AutoML — 21 citations into it
• Optimization & Training — 19 citations into it
• Model Architectures — 14 citations into it
• Management Science and Operations Research — 10 citations into it
• Evaluation & Benchmarks — 9 citations into it

Whom Binxin Ru trusts overall

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

1. Yoshua Bengio
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Barret Zoph
5. Kaiming He
6. Aaron Klein
7. James Bergstra
8. Quoc V. Le
9. Frank Hutter
10. Karen Simonyan

Papers from Binxin Ru's perspective

Ordered by how strongly the researchers Binxin Ru 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel (2020) — 22 citations
• Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search (2020) — 16 citations