Xiaotong Zhang

Artificial Intelligence · with 刘晗 · 2013–2021

A researcher in the Science corpus: 11 papers; trusts 286 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 158 citations into it; #12,827 of 35,345 by trust here, #16,771 by citations
• Computer Vision and Pattern Recognition — 82 citations into it; #10,025 of 21,575 by trust here, #15,955 by citations
• Representation & Self-Supervised Learning — 64 citations into it
• Graph Learning — 33 citations into it
• Statistical and Nonlinear Physics — 24 citations into it
• Signal Processing — 16 citations into it
• Computational Mechanics — 15 citations into it
• Molecular Biology — 15 citations into it

Whom Xiaotong Zhang trusts overall

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

1. Quanquan Gu
2. Xiao-Lei Zhang
3. Geoffrey E. Hinton
4. Inderjit S. Dhillon
5. Diederik P. Kingma
6. Yoshua Bengio
7. Xianchao Zhang
8. Jianwen Zhang
9. Michael I. Jordan
10. Chris H. Q. Ding

Who trusts Xiaotong Zhang overall

1. Xianchao Zhang
2. Yu Zhang
3. Qiang Yang
4. 刘晗
5. Hao Zhu

Papers from Xiaotong Zhang's perspective

Ordered by how strongly the researchers Xiaotong Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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

• Reconstructing Capsule Networks for Zero-shot Intent Classification (2019) — 49 citations
• Label Efficient Semi-Supervised Learning via Graph Filtering (2019) — 179 citations
• Analyzing the correlation between visual space and residents' psychology in Wuhan, China using street-view images and deep-learning technique (2021) — 130 citations
• Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification (2020) — 99 citations
• Attributed Graph Clustering via Adaptive Graph Convolution (2019) — 349 citations
• Multi-Task Clustering with Model Relation Learning (2018) — 22 citations
• Multi-Task Multi-View Clustering (2016) — 79 citations
• Self-Adapted Multi-Task Clustering (2016) — 34 citations
• Smart Multitask Bregman Clustering and Multitask Kernel Clustering (2015) — 25 citations
• Multi-Task Multi-View Clustering for Non-Negative Data (2015) — 40 citations
• Smart Multi-Task Bregman Clustering and Multi-Task Kernel Clustering (2013) — 15 citations