刘晗

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 9 papers; trusts 256 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 155 citations into it; #22,379 of 35,345 by trust here, #18,586 by citations
• Computer Vision and Pattern Recognition — 75 citations into it
• Representation & Self-Supervised Learning — 61 citations into it
• Graph Learning — 33 citations into it
• Statistical and Nonlinear Physics — 23 citations into it
• Molecular Biology — 15 citations into it
• Signal Processing — 15 citations into it
• Computational Mechanics — 14 citations into it

Whom 刘晗 trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Tomas Mikolov
7. Andrew Y. Ng
8. Kaiming He
9. Ilya Sutskever
10. Jimmy Ba

Who trusts 刘晗 overall

1. Xiaotong Zhang
2. Yu Zhang
3. Xianchao Zhang
4. Xuandong Zhao
5. Guangfeng Yan
6. Qiang Yang
7. Hao Zhu

Papers from 刘晗's perspective

Ordered by how strongly the researchers 刘晗 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
• 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