Julien-Charles Levesque

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #27,617 of 35,345 by trust here, #29,412 by citations
• Optimization & Training — 20 citations into it
• Computational Theory and Mathematics — 9 citations into it; #9,573 of 12,182 by trust here, #8,756 by citations
• Management Science and Operations Research — 5 citations into it

Whom Julien-Charles Levesque trusts overall

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

1. James Bergstra
2. Frank Hutter
3. Jasper Snoek
4. Yoshua Bengio
5. Subhash C. Bagui
6. Nikolaus Hansen
7. Matthias Feurer
8. Aaron Klein
9. Geoffrey E. Hinton
10. Iain Murray

Who trusts Julien-Charles Levesque overall

1. Martin Wistuba
2. Nicolas Schilling

Papers from Julien-Charles Levesque's perspective

Ordered by how strongly the researchers Julien-Charles Levesque 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. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Bayesian Hyperparameter Optimization for Ensemble Learning (2016) — 63 citations
• Bayesian optimization for conditional hyperparameter spaces (2017) — 44 citations