Kun Xu

Artificial Intelligence · with Yu · 2001–2020

A researcher in the Science corpus: 13 papers; trusts 629 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 284 citations into it; #18,745 of 35,345 by trust here, #7,346 by citations
• Computer Vision and Pattern Recognition — 204 citations into it
• Natural Language Processing — 91 citations into it
• Generative Models — 86 citations into it
• Probabilistic & Bayesian Methods — 62 citations into it
• Safety, Robustness & Interpretability — 61 citations into it
• Signal Processing — 51 citations into it
• Representation & Self-Supervised Learning — 47 citations into it

Whom Kun 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. Yoshua Bengio
5. Yann LeCun
6. Kaiming He
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Ian J. Goodfellow
10. Alex Graves

Who trusts Kun Xu overall

1. Yuhao Zhang
2. Zhijiang Guo
3. Yanping Chen
4. Arzoo Katiyar
5. Mo Yu
6. Xiaotian Jiang
7. Satoshi Iizuka
8. Guoshun Nan
9. Haoyu Wang
10. Siva Reddy

Papers from Kun Xu's perspective

Ordered by how strongly the researchers Kun 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Efficient affinity-based edit propagation using K-D tree (2009) — 166 citations
• Improving Adversarial Robustness via Promoting Ensemble Diversity (2019) — 504 citations
• Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling (2015) — 303 citations
• Question Answering on Freebase via Relation Extraction and Textual Evidence (2016) — 303 citations
• Structural Information Preserving for Graph-to-Text Generation (2020) — 58 citations
• Boosting Adversarial Training with Hypersphere Embedding (2020) — 170 citations
• EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases (2001) — 108 citations
• The media inequality: Comparing the initial human-human and human-AI social interactions (2017) — 298 citations
• Efficient Learning of Generative Models via Finite-Difference Score Matching (2020) — 65 citations
• Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models (2020) — 10 citations
• DurIAN: Duration Informed Attention Network for Speech Synthesis (2020) — 80 citations
• Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers (2019) — 104 citations
• Triple Generative Adversarial Networks (2019) — 57 citations