Jianqiao Li

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 190 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 85 citations into it
• Artificial Intelligence — 71 citations into it
• Generative Models — 50 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Meta & Continual Learning — 13 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Statistics and Probability — 7 citations into it

Whom Jianqiao Li trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Radford M. Neal
5. Alex Krizhevsky
6. Kaiming He
7. Yann LeCun
8. Max Welling
9. Ilya Sutskever
10. Individualized Treat

Who trusts Jianqiao Li overall

1. Yibo Yang
2. Paris Perdikaris

Papers from Jianqiao Li's perspective

Ordered by how strongly the researchers Jianqiao Li 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet Large Scale Visual Recognition Challenge
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• GAN Memory with No Forgetting (2020) — 151 citations
• Adversarial Learning of a Sampler Based on an Unnormalized Distribution (2019) — 10 citations
• Learning to Sample with Adversarially Learned Likelihood-Ratio (2018) — 14 citations