Zongwei Zhou

Artificial Intelligence · Journal of machine learning research · 2017–2023

A researcher in the Science corpus: 10 papers; trusts 299 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 370 citations into it
• Computer Vision and Pattern Recognition — 194 citations into it; #6,331 of 21,575 by trust here, #748 by citations
• Model Architectures — 49 citations into it
• Optimization & Training — 35 citations into it
• Media Technology — 7 citations into it
• Biophysics — 6 citations into it

Whom Zongwei Zhou trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Yoshua Bengio
6. Evan Shelhamer
7. Ilya Sutskever
8. Yann LeCun
9. Diederik P. Kingma
10. X. Zhang

Who trusts Zongwei Zhou overall

1. Deng-Ping Fan
2. Sheng Fang
3. Ge-Peng Ji
4. Tao Zhou
5. Shunyi Zheng
6. Jianlin Su
7. Valerio Marsocci
8. Kaiwen Zhang
9. Zipeng Qi
10. Hasib Zunair

Papers from Zongwei Zhou's perspective

Ordered by how strongly the researchers Zongwei Zhou 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• PaLM: Scaling Language Modeling with Pathways (2022) — 8,214 citations
• GLaM: Efficient Scaling of Language Models with Mixture-of-Experts (2021) — 1,261 citations
• Overlap Communication with Dependent Computation via Decomposition in Large Deep Learning Models (2022) — 117 citations
• UNet++: A Nested U-Net Architecture for Medical Image Segmentation (2018) — 9,204 citations
• BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition (2021) — 208 citations
• UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation (2019) — 3,790 citations
• Scale MLPerf-0.6 models on Google TPU-v3 Pods (2019) — 43 citations
• CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection (2023) — 356 citations
• Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis (2019) — 406 citations
• Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally (2017) — 409 citations