Jimin Liang

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 54 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Neural Architecture Search & AutoML — 15 citations into it
• Model Architectures — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Graph Learning — 6 citations into it
• Optimization & Training — 6 citations into it

Whom Jimin Liang trusts overall

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

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

Papers from Jimin Liang's perspective

Ordered by how strongly the researchers Jimin Liang 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. Learning Multiple Layers of Features from Tiny Images
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• NPENAS: Neural Predictor Guided Evolution for Neural Architecture Search (2022) — 127 citations
• Medical Image Segmentation based on U-Net: A Review (2020) — 495 citations