Kalifou René Traoré

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #19,456 of 35,345 by trust here, #19,873 by citations
• Reinforcement Learning — 38 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Representation & Self-Supervised Learning — 18 citations into it

Whom Kalifou René Traoré trusts overall

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

1. Timothée Lesort
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Andrei A. Rusu
5. Yoshua Bengio
6. Alex Krizhevsky
7. R. Caruana
8. Kaiming He
9. Yann LeCun
10. J. Urgen Schmidhuber

Who trusts Kalifou René Traoré overall

1. Timothée Lesort
2. Alexandre Heuillet
3. Hugo Caselles-Dupré
4. Maciej Wolczyk
5. Natalia Díaz Rodríguez
6. David Filliat
7. Arthur Douillard
8. Fabien Couthouis

Papers from Kalifou René Traoré's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning (2018) — 35 citations
• Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics (2018) — 62 citations
• DisCoRL: Continual Reinforcement Learning via Policy Distillation (2019) — 66 citations