Sébastien Ehrhardt

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 343 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 96 citations into it; #16,460 of 21,575 by trust here, #12,992 by citations
• Artificial Intelligence — 73 citations into it; #25,032 of 35,345 by trust here, #15,236 by citations
• Representation & Self-Supervised Learning — 34 citations into it
• Model Architectures — 11 citations into it
• Media Technology — 5 citations into it

Whom Sébastien Ehrhardt trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yann LeCun
5. Karen Simonyan
6. Kaiming He
7. Yoshua Bengio
8. Ilya Sutskever
9. Sepp Hochreiter
10. J. Urgen Schmidhuber

Who trusts Sébastien Ehrhardt overall

1. Michael Janner
2. Nicholas Watters
3. Kai Han
4. Jiajun Wu
5. K. J. Joseph
6. Zhun Zhong
7. Ronan Riochet
8. Josh Tenenbaum
9. Sergey Levine

Papers from Sébastien Ehrhardt's perspective

Ordered by how strongly the researchers Sébastien Ehrhardt 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Taking Visual Motion Prediction To New Heightfields (2017) — 24 citations
• Automatically Discovering and Learning New Visual Categories with Ranking Statistics (2020) — 227 citations
• Learning A Physical Long-term Predictor (2017) — 67 citations
• RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces (2020) — 60 citations