Théophile Gaudin
Materials Chemistry · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 32 citations into it; #10,206 of 11,513 by trust here, #6,079 by citations
- Computational Theory and Mathematics — 29 citations into it; #11,593 of 12,182 by trust here, #1,748 by citations
- Computational Chemistry & Drug Discovery — 22 citations into it
- Artificial Intelligence — 21 citations into it
- Molecular Biology — 13 citations into it
- Model Architectures — 12 citations into it
- Natural Language Processing — 11 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
Whom Théophile Gaudin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel M. Lowe
- Alex Graves
- David Weininger
- Ronald J. Williams
- Chin-Yew Lin
- J. Urgen Schmidhuber
- Sepp Hochreiter
- Connor W. Coley
- David Kristjanson Duvenaud
- Wengong Jin
Who trusts Théophile Gaudin overall
Papers from Théophile Gaudin's perspective
Ordered by how strongly the researchers Théophile Gaudin trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)