Alice Schoenauer Sebag

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 118 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it
• Computer Vision and Pattern Recognition — 36 citations into it
• Representation & Self-Supervised Learning — 29 citations into it
• Optimization & Training — 22 citations into it
• Model Architectures — 5 citations into it

Whom Alice Schoenauer Sebag trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Yann LeCun
7. Matthew D. Zeiler
8. Karen Simonyan
9. Kaiming He
10. Sergey Ioffe

Who trusts Alice Schoenauer Sebag overall

1. Toshihiko Matsuura
2. Sharan Vaswani
3. Ioana Bica
4. Tatsuya Harada
5. Aaron Mishkin

Papers from Alice Schoenauer Sebag's perspective

Ordered by how strongly the researchers Alice Schoenauer Sebag 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Multi-Domain Adversarial Learning (2019) — 65 citations
• Stochastic Gradient Descent: Going As Fast As Possible But Not Faster (2017) — 14 citations