Si Si

Artificial Intelligence · with Hsieh · 2012–2020

A researcher in the Science corpus: 6 papers; trusts 193 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 85 citations into it; #16,587 of 35,345 by trust here, #8,077 by citations
• Computer Vision and Pattern Recognition — 48 citations into it; #18,896 of 21,575 by trust here, #15,162 by citations
• Optimization & Training — 29 citations into it
• Model Architectures — 25 citations into it; #1,973 of 2,278 by trust here, #1,620 by citations
• Representation & Self-Supervised Learning — 16 citations into it
• Computational Mechanics — 11 citations into it
• Statistical and Nonlinear Physics — 10 citations into it
• Statistical Learning Theory — 9 citations into it

Whom Si Si trusts overall

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

1. Geoffrey E. Hinton
2. Chih-Jen Lin
3. Alex Krizhevsky
4. Michael W. Mahoney
5. Kaiming He
6. Ali Rahimi
7. Yoshua Bengio
8. Alex Smola
9. Christopher K. I. Williams
10. Quoc V. Le

Who trusts Si Si overall

1. Alexander Litvinenko
2. Yunyang Xiong
3. Alessandro Rudi
4. Ying Sun
5. Hongyu Ren
6. Yong Zhuang
7. Wei-Sheng Chin
8. Cho-Jui Hsieh
9. Ji Zhao
10. Zhanpeng Zeng

Papers from Si Si's perspective

Ordered by how strongly the researchers Si Si 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. 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. 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

• You Look Twice: GaterNet for Dynamic Filter Selection in CNNs (2018) — 111 citations
• Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks (2019) — 1,573 citations
• Multi-Stage Influence Function (2020) — 21 citations
• Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems (2012) — 294 citations
• Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise (2019) — 171 citations
• Memory Efficient Kernel Approximation (2014) — 155 citations