Xu He

Artificial Intelligence · with Jaeger · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 47 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #34,070 of 35,345 by trust here, #12,387 by citations
• Computer Vision and Pattern Recognition — 27 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Meta & Continual Learning — 12 citations into it; #72 of 1,041 by trust here, #176 by citations
• Optimization & Training — 12 citations into it
• Model Architectures — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Xu He trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ian J. Goodfellow
7. J. Urgen Schmidhuber
8. Herbert Jaeger
9. Ilya Sutskever
10. Ruslan Salakhutdinov

Who trusts Xu He overall

1. Zixuan Ke
2. Mehrdad Farajtabar
3. Bing Liu
4. Seyed Iman Mirzadeh
5. Johannes von Oswald
6. Mengmi Zhang
7. Zheda Mai
8. Timothée Lesort
9. Tianlin Liu
10. Hu Xu

Papers from Xu He's perspective

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

Their papers

• Task Agnostic Continual Learning via Meta Learning (2019) — 103 citations
• Overcoming Catastrophic Interference by Conceptors (2017) — 14 citations
• Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation (2018) — 128 citations