Boxi Wu

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 125 citations into it
• Safety, Robustness & Interpretability — 75 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Molecular Biology — 9 citations into it
• Optimization & Training — 9 citations into it
• Electrical and Electronic Engineering — 8 citations into it

Whom Boxi Wu trusts overall

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

1. Alex Krizhevsky
2. Francesco Croce
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Ian J. Goodfellow
7. Christian Szegedy
8. Diederik P. Kingma
9. Matthias Hein
10. Yann LeCun

Who trusts Boxi Wu overall

1. Omid Nejati Manzari

Papers from Boxi Wu's perspective

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

Their papers

• Improving alignment of dialogue agents via targeted human judgements (2022) — 676 citations
• Do Wider Neural Networks Really Help Adversarial Robustness? (2020) — 106 citations