Jianlong Chang

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 556 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 164 citations into it; #15,997 of 21,575 by trust here, #12,419 by citations
• Artificial Intelligence — 156 citations into it
• Model Architectures — 56 citations into it
• Neural Architecture Search & AutoML — 46 citations into it
• Optimization & Training — 33 citations into it
• Efficiency & Compression — 18 citations into it
• Representation & Self-Supervised Learning — 17 citations into it; #2,456 of 3,145 by trust here, #2,355 by citations
• Generative Models — 16 citations into it

Whom Jianlong Chang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Kaiming He
5. Barret Zoph
6. Diederik P. Kingma
7. Yann LeCun
8. Quoc V. Le
9. Christian Szegedy
10. Ilya Sutskever

Who trusts Jianlong Chang overall

1. Xu Ji
2. Zhun Zhong
3. Raghuram Mandyam Annasamy
4. Xinbang Zhang
5. Andrea Vedaldi
6. Yanbei Chen
7. Ganqu Cui
8. João F. Henriques
9. Wouter Van Gansbeke
10. R. Devon Hjelm

Papers from Jianlong Chang's perspective

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

• Deep Adaptive Image Clustering (2017) — 553 citations
• Differentiable Architecture Search with Ensemble Gumbel-Softmax (2019) — 20 citations
• Spatio-Temporal Graph Structure Learning for Traffic Forecasting (2020) — 301 citations
• DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling (2020) — 15 citations
• Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification (2020) — 369 citations
• DATA: Differentiable ArchiTecture Approximation (2019) — 56 citations