Jinwen Ma

Artificial Intelligence · 2004–2021

A researcher in the Science corpus: 8 papers; trusts 235 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 161 citations into it; #10,108 of 35,345 by trust here, #15,866 by citations
• Computer Vision and Pattern Recognition — 90 citations into it; #16,764 of 21,575 by trust here, #16,787 by citations
• Meta & Continual Learning — 39 citations into it; #448 of 1,041 by trust here, #355 by citations
• Representation & Self-Supervised Learning — 36 citations into it
• Optimization & Training — 19 citations into it
• Statistics and Probability — 19 citations into it
• Model Architectures — 17 citations into it
• Computer Networks and Communications — 13 citations into it

Whom Jinwen Ma trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Kaiming He
6. Diederik P. Kingma
7. Ilya Sutskever
8. L. Eon Bottou
9. Ross B. Girshick
10. J. Urgen Schmidhuber

Who trusts Jinwen Ma overall

1. Jingyi Shen
2. Omer Berat Sezer
3. Gyuhak Kim
4. Ze Hu
5. Jiayu Qiu
6. Qi Qin
7. Wenpeng Hu
8. Yiduo Guo
9. M. Ugur Gudelek
10. Bing Liu

Papers from Jinwen Ma's perspective

Ordered by how strongly the researchers Jinwen Ma 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DrugComboRanker: drug combination discovery based on target network analysis (2014) — 158 citations
• CNN-LSTM Neural Network Model for Quantitative Strategy Analysis in Stock Markets (2017) — 99 citations
• Continual Learning by Using Information of Each Class Holistically (2021) — 66 citations
• HRN: A Holistic Approach to One Class Learning (2020) — 71 citations
• The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects (2018) — 292 citations
• Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation (2018) — 150 citations
• Multiple Nuclei Tracking Using Integer Programming for Quantitative Cancer Cell Cycle Analysis (2010) — 138 citations
• Learning to cluster web search results (2004) — 688 citations