Shu-Huan Chang
Artificial Intelligence · 2018–2025
A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 25 citations into it
- Reinforcement Learning — 20 citations into it; #2,150 of 2,242 by trust here, #1,609 by citations
- Computer Vision and Pattern Recognition — 17 citations into it
Whom Shu-Huan Chang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chelsea Finn
- Alex Krizhevsky
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Pieter Abbeel
- Sergey Levine
- Jan Peters
- Ilya Sutskever
- Brian D. Ziebart
Who trusts Shu-Huan Chang overall
- Gaurav Menghani
- Dimitrios Stamoulis
- Xiangxiang Chu
- Mingxing Tan
- Jianlong Chang
- Sheng-Chun Kao
- Xinbang Zhang
- Martin Wistuba
- Chris Zhang
- Ting-Wu Chin
Papers from Shu-Huan Chang's perspective
Ordered by how strongly the researchers Shu-Huan Chang 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Task Transfer by Preference-Based Cost Learning (2018) — 56 citations
- Seed1.5-VL Technical Report (2025) — 350 citations
- MONAS: Multi-Objective Neural Architecture Search using Reinforcement Learning (2018) — 149 citations