Weihao Kong

Artificial Intelligence · 2012–2023

A researcher in the Science corpus: 6 papers; trusts 201 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 35 citations into it; #19,937 of 21,575 by trust here, #18,782 by citations
• Signal Processing — 31 citations into it
• Management Science and Operations Research — 28 citations into it
• Statistics and Probability — 18 citations into it
• Information Retrieval & Search — 14 citations into it
• Statistical Learning Theory — 11 citations into it
• Time-Series & Forecasting — 9 citations into it

Whom Weihao Kong trusts overall

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

1. Alex Krizhevsky
2. Antonio Torralba
3. Geoffrey E. Hinton
4. Svetlana Lazebnik
5. Yunchao Gong
6. Diederik P. Kingma
7. Jun Wang
8. Yoshua Bengio
9. Aude Oliva
10. Kaiming He

Who trusts Weihao Kong overall

1. Wei David Liu
2. Wu-Jun Li
3. Dongjin Song
4. Fumin Shen
5. Jingdong Wang
6. Qing-Yuan Jiang
7. Huihui Wei
8. Ting Zhang
9. Tiezheng Ge
10. Jingkuan Song

Papers from Weihao Kong's perspective

Ordered by how strongly the researchers Weihao Kong 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Manhattan hashing for large-scale image retrieval (2012) — 109 citations
• A decoder-only foundation model for time-series forecasting (2023) — 785 citations
• Long-term Forecasting with TiDE: Time-series Dense Encoder (2023) — 600 citations
• Efficient Algorithms and Lower Bounds for Robust Linear Regression (2018) — 174 citations
• Learning Populations of Parameters (2017) — 36 citations
• Isotropic Hashing (2012) — 331 citations