Shutao Xia
Artificial Intelligence · with Wang · 2018–2021
A researcher in the Science corpus: 9 papers; trusts 698 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 265 citations into it; #20,813 of 35,345 by trust here, #7,657 by citations
- Computer Vision and Pattern Recognition — 216 citations into it; #11,500 of 21,575 by trust here, #5,565 by citations
- Safety, Robustness & Interpretability — 108 citations into it; #762 of 2,251 by trust here, #1,290 by citations
- Optimization & Training — 49 citations into it
- Model Architectures — 47 citations into it
- Signal Processing — 47 citations into it
- Media Technology — 30 citations into it; #1,989 of 3,621 by trust here, #910 by citations
- Representation & Self-Supervised Learning — 25 citations into it
Whom Shutao Xia trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yann LeCun
- Yoshua Bengio
- Christian Szegedy
- Diederik P. Kingma
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
Who trusts Shutao Xia overall
- Sylvestre-Alvise Rebuffi
- Sven Gowal
- Matthew Norton
- David Stutz
- Anqi Mao
- Yaowei Zheng
- Xingjun Ma
- Yisen Wang
- Danruo Deng
- Junnan Li
Papers from Shutao Xia's perspective
Ordered by how strongly the researchers Shutao Xia trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Second-Order Attention Network for Single Image Super-Resolution (2019) — 1,809 citations
- Dimensionality-Driven Learning with Noisy Labels (2018) — 475 citations
- TokenPose: Learning Keypoint Tokens for Human Pose Estimation (2021) — 388 citations
- Iterative Learning with Open-set Noisy Labels (2018) — 357 citations
- Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets (2020) — 364 citations
- Backdoor Learning: A Survey (2020) — 841 citations
- Adversarial Weight Perturbation Helps Robust Generalization (2020) — 894 citations
- Adversarial Defense Via Local Flatness Regularization (2019) — 21 citations
- Adaptive Regularization of Labels (2019) — 33 citations