Erwan Le Merrer

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 84 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 77 citations into it; #13,083 of 35,345 by trust here, #16,771 by citations
• Computer Vision and Pattern Recognition — 39 citations into it; #8,587 of 21,575 by trust here, #11,286 by citations
• Safety, Robustness & Interpretability — 30 citations into it
• Optimization & Training — 27 citations into it
• Generative Models — 13 citations into it
• Safety Research — 11 citations into it
• Computer Networks and Communications — 9 citations into it
• Information Systems — 9 citations into it

Whom Erwan Le Merrer trusts overall

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

1. Yann LeCun
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ian J. Goodfellow
5. Judea Pearl
6. Diederik P. Kingma
7. Florian Tramèr
8. Yoshua Bengio
9. Christian Szegedy
10. Kaiming He

Who trusts Erwan Le Merrer overall

1. Huili Chen
2. Bita Darvish Rouhani
3. Abhishek Chakraborty
4. Mingfu Xue
5. Sebastian Szyller
6. Lixu Wang
7. Farinaz Koushanfar
8. Jingwen Ye
9. Ankit Mondal
10. Aleksei Triastcyn

Papers from Erwan Le Merrer's perspective

Ordered by how strongly the researchers Erwan Le Merrer 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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• The Bouncer Problem: Challenges to Remote Explainability (2019) — 9 citations
• MD-GAN: Multi-Discriminator Generative Adversarial Networks for Distributed Datasets (2018) — 226 citations
• Distributed deep learning on edge-devices: Feasibility via adaptive compression (2017) — 70 citations
• Adversarial frontier stitching for remote neural network watermarking (2017) — 398 citations