Yunpeng Pan

Artificial Intelligence · 2014–2017

A researcher in the Science corpus: 6 papers; trusts 69 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 58 citations into it; #32,060 of 35,345 by trust here, #15,004 by citations
• Reinforcement Learning — 51 citations into it; #803 of 2,242 by trust here, #1,371 by citations
• Optimization & Training — 29 citations into it
• Control and Systems Engineering — 25 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Statistical Learning Theory — 18 citations into it
• Probabilistic & Bayesian Methods — 17 citations into it; #657 of 1,525 by trust here, #1,136 by citations
• Robotics & Control — 16 citations into it

Whom Yunpeng Pan trusts overall

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

1. Marc Peter Deisenroth
2. Geoffrey E. Hinton
3. Richard S. Sutton
4. Stéphane Ross
5. Dean A. Pomerleau
6. Carl E. Rasmussen
7. E. Todorov
8. Sham M. Kakade
9. Sergey Levine
10. Pieter Abbeel

Who trusts Yunpeng Pan overall

1. Ching-An Cheng
2. Sanket Kamthe
3. Niklas Wahlstrom
4. Bo Dai
5. Marc Peter Deisenroth
6. Keuntaek Lee
7. J. A. G. Higuera
8. Lukas Hewing
9. Xinyan Yan
10. Manuel Watter

Papers from Yunpeng Pan's perspective

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

Their papers

• Agile Autonomous Driving using End-to-End Deep Imitation Learning (2017) — 285 citations
• Learning from Conditional Distributions via Dual Kernel Embeddings (2016) — 21 citations
• Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning (2017) — 54 citations
• Appendix for the Paper : Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control (2017)
• Learning from Conditional Distributions via Dual Embeddings (2016) — 136 citations
• Probabilistic Differential Dynamic Programming (2014) — 109 citations