Minghao Xu

Artificial Intelligence · with Zhang · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 209 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 81 citations into it
• Computer Vision and Pattern Recognition — 63 citations into it
• Representation & Self-Supervised Learning — 57 citations into it
• Molecular Biology — 46 citations into it
• Computational Biology & Bioinformatics — 27 citations into it
• Graph Learning — 16 citations into it
• Generative Models — 8 citations into it
• Optimization & Training — 7 citations into it

Whom Minghao Xu trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. Ilya Sutskever
8. Ross B. Girshick
9. Max Welling
10. Karen Simonyan

Who trusts Minghao Xu overall

1. Yusuke Iwasawa
2. Divyat Mahajan
3. Daehee Kim
4. Jaemin Na
5. Yutaka Matsuo
6. Shruti Tople

Papers from Minghao Xu's perspective

Ordered by how strongly the researchers Minghao Xu 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. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Adversarial Domain Adaptation with Domain Mixup (2019) — 509 citations
• Protein Representation Learning by Geometric Structure Pretraining (2022) — 328 citations
• Variational Few-Shot Learning (2019) — 168 citations