Joey Tianyi Zhou

Artificial Intelligence · 2014–2022

A researcher in the Science corpus: 16 papers; trusts 1,071 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 282 citations into it; #14,732 of 35,345 by trust here, #7,531 by citations
• Computer Vision and Pattern Recognition — 279 citations into it; #13,296 of 21,575 by trust here, #6,795 by citations
• Representation & Self-Supervised Learning — 93 citations into it
• Natural Language Processing — 58 citations into it
• Signal Processing — 49 citations into it
• Safety, Robustness & Interpretability — 47 citations into it; #724 of 2,251 by trust here, #816 by citations
• Optimization & Training — 30 citations into it
• Evaluation & Benchmarks — 29 citations into it

Whom Joey Tianyi Zhou trusts overall

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

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

Who trusts Joey Tianyi Zhou overall

1. Yong Kiam Tan
2. Gabriella Csurka
3. Seungwhan Moon
4. Linyang Li
5. Xinxing Xu
6. Tianshui Chen
7. Jianfeng Feng
8. Adyasha Maharana
9. Siddhant Garg
10. Wei-Yu Chen

Papers from Joey Tianyi Zhou's perspective

Ordered by how strongly the researchers Joey Tianyi Zhou 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. 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. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment (2019) — 1,382 citations
• Contrastive Clustering (2021) — 831 citations
• Span-based Localizing Network for Natural Language Video Localization (2020) — 402 citations
• Exploit Bounding Box Annotations for Multi-Label Object Recognition (2015) — 181 citations
• AnomalyNet: An Anomaly Detection Network for Video Surveillance (2019) — 317 citations
• Trusted Multi-View Classification With Dynamic Evidential Fusion (2022) — 474 citations
• Deep Partial Multi-View Learning (2020) — 315 citations
• You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network (2020) — 282 citations
• Query-efficient Meta Attack to Deep Neural Networks (2019) — 88 citations
• COMIC: Multi-view Clustering Without Parameter Selection (2019) — 358 citations
• Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment (2019)
• Structured AutoEncoders for Subspace Clustering (2018) — 326 citations
• Transfer Hashing with Privileged Information (2016) — 29 citations
• Simple and Efficient Learning using Privileged Information (2016) — 12 citations
• Hybrid Heterogeneous Transfer Learning through Deep Learning (2014) — 181 citations
• Heterogeneous Domain Adaptation for Multiple Classes (2014) — 159 citations