Mathieu Germain

Artificial Intelligence · 2015–2017

A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 105 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #4,045 of 35,345 by trust here, #5,281 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #3,298 of 21,575 by trust here, #4,988 by citations
• Generative Models — 11 citations into it; #353 of 1,956 by trust here, #549 by citations
• Model Architectures — 11 citations into it
• Optimization & Training — 10 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Mathieu Germain trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Matthew D. Zeiler
4. Ruslan Salakhutdinov
5. Diederik P. Kingma
6. Yann LeCun
7. Alex Krizhevsky
8. Richard S. Sutton
9. John C. Duchi
10. Iain Murray

Who trusts Mathieu Germain overall

1. Diederik P. Kingma
2. Yang Song
3. George Papamakarios
4. Emiel Hoogeboom
5. Charlie Nash
6. Max Welling
7. Yoshua Bengio
8. Chin-Wei Huang
9. Aäron van den Oord
10. Joeri Hermans

Papers from Mathieu Germain's perspective

Ordered by how strongly the researchers Mathieu Germain 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. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• MADE: Masked Autoencoder for Distribution Estimation (2015) — 978 citations
• A Deep Reinforcement Learning Chatbot (2017) — 245 citations
• Theano: A Python framework for fast computation of mathematical expressions (2016) — 2,380 citations
• Proceedings of The 32nd International Conference on Machine Learning (2015) — 136 citations