Junjiao Tian

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 222 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 95 citations into it
• Computer Vision and Pattern Recognition — 73 citations into it
• Meta & Continual Learning — 36 citations into it
• Reinforcement Learning — 25 citations into it
• Model Architectures — 13 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Natural Language Processing — 10 citations into it
• Optimization & Training — 10 citations into it

Whom Junjiao Tian trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ross B. Girshick
7. Yann LeCun
8. X. Zhang
9. Ilya Sutskever
10. Shaoqing Ren

Who trusts Junjiao Tian overall

1. Yiming Li
2. Yue Hu

Papers from Junjiao Tian's perspective

Ordered by how strongly the researchers Junjiao Tian 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Who2com: Collaborative Perception via Learnable Handshake Communication (2020) — 261 citations
• When2com: Multi-Agent Perception via Communication Graph Grouping (2020) — 340 citations
• A Closer Look at Rehearsal-Free Continual Learning * (2022) — 88 citations