Sébastien M. R. Arnold

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 57 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Optimization & Training — 11 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Meta & Continual Learning — 7 citations into it
• Reinforcement Learning — 5 citations into it

Whom Sébastien M. R. Arnold trusts overall

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

1. Richard S. Sutton
2. Chelsea Finn
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. N. Schraudolph
6. Oriol Vinyals
7. Robert A. Jacobs
8. Diederik P. Kingma
9. J. Urgen Schmidhuber
10. Alex Krizhevsky

Who trusts Sébastien M. R. Arnold overall

1. Da-Wei Zhou

Papers from Sébastien M. R. Arnold's perspective

Ordered by how strongly the researchers Sébastien M. R. Arnold 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (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

• When MAML Can Adapt Fast and How to Assist When It Cannot (2019) — 31 citations