Pingchuan Ma

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 4 papers; trusts 169 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Signal Processing — 35 citations into it; #4,585 of 7,572 by trust here, #4,560 by citations
• Computer Vision and Pattern Recognition — 31 citations into it; #18,728 of 21,575 by trust here, #17,757 by citations
• Optimization & Training — 11 citations into it
• Computational Mechanics — 10 citations into it
• Computer Graphics and Computer-Aided Design — 9 citations into it
• Model Architectures — 9 citations into it
• Reinforcement Learning — 8 citations into it

Whom Pingchuan Ma trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Joon Son Chung
6. Andrew Zisserman
7. Yoshua Bengio
8. Ilya Sutskever
9. John Schulman
10. Yann LeCun

Who trusts Pingchuan Ma overall

1. Wei-Ning Hsu
2. Paul Garnier
3. Ruohan Gao
4. Stavros Petridis
5. Triantafyllos Afouras
6. Bowen Shi
7. Tal Remez
8. Jinyu Li

Papers from Pingchuan Ma's perspective

Ordered by how strongly the researchers Pingchuan Ma trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Lipreading Using Temporal Convolutional Networks (2020) — 307 citations
• End-To-End Audio-Visual Speech Recognition with Conformers (2021) — 311 citations
• End-to-End Audiovisual Speech Recognition (2018) — 297 citations
• Fluid directed rigid body control using deep reinforcement learning (2018) — 77 citations