Sheng Li

Computer Vision and Pattern Recognition · with Fu · 2015–2020

A researcher in the Science corpus: 8 papers; trusts 721 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 152 citations into it
• Artificial Intelligence — 143 citations into it
• Statistics and Probability — 100 citations into it
• Natural Language Processing — 70 citations into it
• Causal Inference & Discovery — 52 citations into it
• Multimodal Learning — 50 citations into it
• Optimization & Training — 25 citations into it
• Representation & Self-Supervised Learning — 25 citations into it

Whom Sheng Li trusts overall

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

1. Donald B. Rubin
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Ruslan Salakhutdinov
6. Ilya Sutskever
7. Diederik P. Kingma
8. Kaiming He
9. Oriol Vinyals
10. Ross B. Girshick

Who trusts Sheng Li overall

1. Ahmed M. Alaa
2. Ioana Bica
3. Hao Wang
4. Mihaela van der Schaar
5. Xiangnan He
6. Dietmar Jannach
7. Lovedeep Gondara
8. Yongfeng Zhang
9. Wonsung Lee
10. Kun Kuang

Papers from Sheng Li's perspective

Ordered by how strongly the researchers Sheng Li 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• A domain-specific supercomputer for training deep neural networks (2020) — 294 citations
• Scene Graph Generation With External Knowledge and Image Reconstruction (2019) — 321 citations
• Visual to Text: Survey of Image and Video Captioning (2019) — 106 citations
• A Survey on Causal Inference (2020) — 690 citations
• Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit (2019) — 21 citations
• Representation Learning for Treatment Effect Estimation from Observational Data (2018) — 348 citations
• Matching on Balanced Nonlinear Representations for Treatment Effects Estimation (2017) — 75 citations
• Deep Collaborative Filtering via Marginalized Denoising Auto-encoder (2015) — 483 citations