Yuanshun Yao
Artificial Intelligence · with Zhao · 2015–2023
A researcher in the Science corpus: 6 papers; trusts 114 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 135 citations into it; #22,894 of 35,345 by trust here, #7,241 by citations
- Safety, Robustness & Interpretability — 84 citations into it
- Computer Vision and Pattern Recognition — 47 citations into it
- Signal Processing — 47 citations into it; #5,235 of 7,572 by trust here, #888 by citations
- Natural Language Processing — 24 citations into it
- Information Systems — 20 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Optimization & Training — 7 citations into it
Whom Yuanshun Yao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yann LeCun
- Alex Graves
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Ian J. Goodfellow
- Kaiming He
- Nicholas Carlini
Who trusts Yuanshun Yao overall
- Yige Li
- David Marco Sommer
- Nektaria Kaloudi
- Xiaojun Xu
- Nicholas Carlini
- Ahmed Salem
- Steven Y. Feng
- Lingjuan Lyu
- Bo Liu
- Xingjun Ma
Papers from Yuanshun Yao's perspective
Ordered by how strongly the researchers Yuanshun Yao trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks (2019) — 1,894 citations
- Automated Crowdturfing Attacks and Defenses in Online Review Systems (2017) — 169 citations
- Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment (2023) — 575 citations
- Latent Backdoor Attacks on Deep Neural Networks (2019) — 478 citations
- With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning (2018) — 126 citations
- A daily global mesoscale ocean eddy dataset from satellite altimetry (2015) — 322 citations