Zhen Lin

Artificial Intelligence · 2018–2023

A researcher in the Science corpus: 2 papers; trusts 73 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it; #7,971 of 21,575 by trust here, #12,172 by citations
• Model Architectures — 16 citations into it; #875 of 2,278 by trust here, #1,601 by citations
• Evaluation & Benchmarks — 8 citations into it
• Natural Language Processing — 8 citations into it
• Safety, Robustness & Interpretability — 7 citations into it
• Computational Mechanics — 6 citations into it
• Computational Chemistry & Drug Discovery — 5 citations into it

Whom Zhen Lin trusts overall

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

1. Diederik P. Kingma
2. Andrey Malinin
3. Geoffrey E. Hinton
4. Yarin Gal
5. Alex Krizhevsky
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Kaiming He
10. Jimmy Ba

Who trusts Zhen Lin overall

1. Maurice Weiler
2. Risi Kondor
3. Chao Chen
4. Johannes Klicpera
5. Yi Liao
6. Taco Cohen
7. Brandon M. Anderson
8. Tess E. Smidt
9. Johannes Brandstetter
10. Simon L. Batzner

Papers from Zhen Lin's perspective

Ordered by how strongly the researchers Zhen Lin 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network (2018) — 315 citations
• Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models (2023) — 322 citations