Rongjun Qin

Artificial Intelligence · with Zhang · 2021

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Reinforcement Learning — 33 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Rongjun Qin trusts overall

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

1. Richard S. Sutton
2. Sergey Levine
3. Aviral Kumar
4. Geoffrey E. Hinton
5. Justin Fu
6. Scott Fujimoto
7. Pieter Abbeel
8. Doina Precup
9. John Schulman
10. Diederik P. Kingma

Papers from Rongjun Qin's perspective

Ordered by how strongly the researchers Rongjun Qin 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Reinforcement Learning: An Introduction
9. Human-level control through deep reinforcement learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning (2021) — 99 citations