Patrick Goebel

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Reinforcement Learning — 24 citations into it
• Robotics & Control — 18 citations into it
• Aerospace Engineering — 13 citations into it

Whom Patrick Goebel trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Kaiming He
5. Yann LeCun
6. Alex Krizhevsky
7. Karen Simonyan
8. Sebastian Thrun
9. Richard S. Sutton
10. Ilya Sutskever

Papers from Patrick Goebel's perspective

Ordered by how strongly the researchers Patrick Goebel 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: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning (2020) — 99 citations
• GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation (2018) — 89 citations
• Deep Local Trajectory Replanning and Control for Robot Navigation (2019) — 72 citations