P. Dupont

Artificial Intelligence · with Helleputte · 2009–2013

A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #35,045 of 35,345 by trust here, #32,362 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #14,183 of 21,575 by trust here, #17,757 by citations
• Molecular Biology — 16 citations into it; #7,886 of 17,773 by trust here, #12,008 by citations
• Representation & Self-Supervised Learning — 13 citations into it; #3,115 of 3,145 by trust here, #3,047 by citations
• Statistical Learning Theory — 6 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom P. Dupont trusts overall

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

1. Isabelle M Guyon
2. Volker Roth
3. Jason Aaron Edward Weston
4. Yvan Saeys
5. Andre´ Elisseeff
6. Geoffrey E. Hinton
7. Bernhard Schölkopf
8. Ludmila I. Kuncheva
9. Vladimir Naumovich Vapnik
10. Josh Tenenbaum

Who trusts P. Dupont overall

1. Jiaxuan Wang
2. Hugh Salimbeni
3. Benoît Frénay

Papers from P. Dupont's perspective

Ordered by how strongly the researchers P. Dupont 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. 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Robust biomarker identification for cancer diagnosis with ensemble feature selection methods (2010) — 597 citations
• Partially supervised feature selection with regularized linear models (2009) — 39 citations
• Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation (2013) — 102 citations
• Robust Multi-Class Gaussian Process Classification (2011) — 69 citations