Yves Chauvin

Model Architectures · 1988–2000

A researcher in the Science corpus: 8 papers; trusts 7 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Model Architectures — 5 citations into it

Whom Yves Chauvin trusts overall

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

1. Radford M. Neal
2. Lawrence R. Rabiner
3. Anders Krogh
4. Arthur P. Dempster
5. Yann LeCun
6. Pierre Baldi
7. Eric B. Baum
8. David John Cameron MacKay
9. Burkhard Rost
10. Yoshua Bengio

Who trusts Yves Chauvin overall

1. Yann LeCun
2. Tim Dettmers
3. James T. Kwok
4. J. Urgen Schmidhuber
5. Mingzhe Chen
6. Rohit Tripathy
7. Namhoon Lee
8. Pierre Baldi
9. Yoshua Bengio
10. Luke S. Zettlemoyer

Papers from Yves Chauvin's perspective

Ordered by how strongly the researchers Yves Chauvin trusts endorse each paper. Same corpus, a different order for every researcher.

1. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
2. A tutorial on hidden Markov models and selected applications in speech recognition
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Assessing the accuracy of prediction algorithms for classification: an overview (2000) — 2,199 citations
• Hybrid Modeling, HMM/NN Architectures, and Protein Applications (1996)
• Backpropagation: theory, architectures, and applications (1995)
• Neural Networks for Fingerprint Recognition (1993)
• Temporal Evolution of Generalization during Learning in Linear Networks (1991)
• Generalization Dynamics in LMS Trained Linear Networks (1990)
• Supervised and Unsupervised Learning in Linear Networks (1990)
• A Back-Propagation Algorithm with Optimal Use of Hidden Units (1988)