Quanzheng Li
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 6 papers; trusts 189 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 119 citations into it; #21,131 of 35,345 by trust here, #4,888 by citations
- Computer Vision and Pattern Recognition — 114 citations into it
- Model Architectures — 43 citations into it; #1,450 of 2,278 by trust here, #1,643 by citations
- Optimization & Training — 23 citations into it
- Media Technology — 10 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Pulmonary and Respiratory Medicine — 9 citations into it
- Oncology — 7 citations into it
Whom Quanzheng Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Karen Simonyan
- Yann LeCun
- Yoshua Bengio
- X. Zhang
- Christian Szegedy
- Ross B. Girshick
- Ilya Sutskever
Who trusts Quanzheng Li overall
Papers from Quanzheng Li's perspective
Ordered by how strongly the researchers Quanzheng Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
Their papers
- Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer (2017) — 3,174 citations
- A generalist vision–language foundation model for diverse biomedical tasks (2023) — 401 citations
- Federated learning for predicting clinical outcomes in patients with COVID-19 (2021) — 736 citations
- From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge (2019) — 709 citations
- Deep Learning-based Image Segmentation on Multimodal Medical Imaging (2019) — 366 citations
- Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations (2017) — 565 citations