Stanislas Lauly

Natural Language Processing · 2012–2017

A researcher in the Science corpus: 3 papers; trusts 36 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 35 citations into it; #1,182 of 5,688 by trust here, #2,243 by citations
• Artificial Intelligence — 34 citations into it; #17,755 of 35,345 by trust here, #10,798 by citations
• Computer Vision and Pattern Recognition — 11 citations into it; #12,950 of 21,575 by trust here, #12,689 by citations
• Representation & Self-Supervised Learning — 8 citations into it
• Model Architectures — 7 citations into it; #432 of 2,278 by trust here, #1,530 by citations
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Stanislas Lauly trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Ruslan Salakhutdinov
4. Hugo Larochelle
5. Xavier Glorot
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Alex Graves
9. Ilya Sutskever
10. Yann LeCun

Who trusts Stanislas Lauly overall

1. Chunyuan Li
2. Yin Zheng
3. Quoc V. Le
4. Ruslan Salakhutdinov
5. Felix Stahlberg
6. Kyunghyun Cho
7. Zhe Gan
8. Hugo Larochelle
9. Benigno Uria
10. Nikolaos Pappas

Papers from Stanislas Lauly's perspective

Ordered by how strongly the researchers Stanislas Lauly 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• An Autoencoder Approach to Learning Bilingual Word Representations (2014) — 348 citations
• Does Neural Machine Translation Benefit from Larger Context? (2017) — 153 citations
• A Neural Autoregressive Topic Model (2012) — 231 citations