Xiaojun Xu

Artificial Intelligence · with Song · 2017–2019

A researcher in the Science corpus: 5 papers; trusts 355 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 201 citations into it; #12,224 of 35,345 by trust here, #11,072 by citations
• Computer Vision and Pattern Recognition — 117 citations into it
• Safety, Robustness & Interpretability — 86 citations into it
• Natural Language Processing — 66 citations into it
• Multimodal Learning — 44 citations into it
• Signal Processing — 39 citations into it
• Model Architectures — 16 citations into it
• Information Systems — 13 citations into it

Whom Xiaojun Xu trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. Oriol Vinyals
9. Christian Szegedy
10. Jimmy Ba

Who trusts Xiaojun Xu overall

1. Tao Yu
2. Rui Zhang
3. Pengcheng Yin
4. Byeong-Hoon So
5. Christopher Baik
6. Eugene Bagdasarian
7. Pengcheng He
8. Ziyu Yao
9. Wonseok Hwang
10. Wenhu Chen

Papers from Xiaojun Xu's perspective

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

Their papers

• SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning (2017) — 508 citations
• Can you fool AI with adversarial examples on a visual Turing test? (2017) — 42 citations
• Detecting AI Trojans Using Meta Neural Analysis (2019) — 395 citations
• Fooling Vision and Language Models Despite Localization and Attention Mechanism (2017) — 88 citations
• Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection (2017) — 700 citations