Ruohan Zhang

Artificial Intelligence · Conference on Robot Learning · 2016–2023

A researcher in the Science corpus: 12 papers; trusts 321 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 262 citations into it
• Computer Vision and Pattern Recognition — 225 citations into it; #19,385 of 21,575 by trust here, #10,905 by citations
• Reinforcement Learning — 163 citations into it
• Control and Systems Engineering — 93 citations into it
• Robotics & Control — 48 citations into it
• Cognitive Neuroscience — 47 citations into it
• Evaluation & Benchmarks — 38 citations into it
• Human-Computer Interaction — 36 citations into it; #949 of 2,253 by trust here, #616 by citations

Whom Ruohan Zhang trusts overall

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

1. Richard S. Sutton
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Yann LeCun
7. Gunnar Farnebäck
8. Pieter Abbeel
9. Kaiming He
10. Ilya Sutskever

Who trusts Ruohan Zhang overall

1. Akanksha Saran
2. Lin Guan
3. Dmitry Nikulin
4. Sihang Guo
5. Scott Niekum
6. Mudit Verma
7. Elaine Schaertl Short
8. Anastasia Ianina
9. Yifeng Zhu
10. Wenlong Huang

Papers from Ruohan Zhang's perspective

Ordered by how strongly the researchers Ruohan Zhang 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. 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. GENERATIVE ADVERSARIAL NETS

Their papers

• AGIL: Learning Attention from Human for Visuomotor Tasks (2018) — 85 citations
• MimicPlay: Long-Horizon Imitation Learning by Watching Human Play (2023) — 343 citations
• Leveraging Human Guidance for Deep Reinforcement Learning Tasks (2019) — 98 citations
• VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models (2023) — 1,011 citations
• BEHAVIOR-1K: A Benchmark for Embodied AI with 1, 000 Everyday Activities and Realistic Simulation (2022) — 370 citations
• Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation (2020) — 56 citations
• Efficiently Guiding Imitation Learning Algorithms with Human Gaze (2020) — 19 citations
• Human Gaze Assisted Artificial Intelligence: A Review (2020) — 82 citations
• Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset (2019) — 82 citations
• Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain (2017) — 5 citations
• Visual Attention Guided Deep Imitation Learning (2017)
• Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain (2016) — 9 citations