Sebastian Starke

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 41 citations into it; #10,803 of 21,575 by trust here, #12,172 by citations
• Control and Systems Engineering — 34 citations into it; #3,610 of 8,257 by trust here, #2,692 by citations
• Artificial Intelligence — 17 citations into it
• Reinforcement Learning — 6 citations into it; #1,929 of 2,242 by trust here, #1,999 by citations
• Model Architectures — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Sebastian Starke trusts overall

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

1. Xue Bin Peng
2. Daniel Holden
3. Alla Safonova
4. Geoffrey E. Hinton
5. Jessica K. Hodgins
6. Djork-Arné Clevert
7. Robert A. Jacobs
8. Michael I. Jordan
9. Sergey Levine
10. Sepp Hochreiter

Who trusts Sebastian Starke overall

1. Omid Taheri
2. Xue Bin Peng
3. Nantheera Anantrasirichai
4. Michael J. Black
5. Xin Chen
6. D. Bull
7. Hung Yu Ling
8. Dimitrios Tzionas
9. Vasileios Choutas
10. Nima Ghorbani

Papers from Sebastian Starke's perspective

Ordered by how strongly the researchers Sebastian Starke 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
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

• Neural state machine for character-scene interactions (2019) — 366 citations
• Mode-adaptive neural networks for quadruped motion control (2018) — 370 citations