Philippe Beaudoin

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 92 citations into it
• Computer Vision and Pattern Recognition — 50 citations into it
• Reinforcement Learning — 41 citations into it
• Representation & Self-Supervised Learning — 32 citations into it
• Model Architectures — 31 citations into it
• Management Science and Operations Research — 7 citations into it
• Optimization & Training — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Philippe Beaudoin trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Richard S. Sutton
5. Ronald J. Williams
6. Yann LeCun
7. Alex Krizhevsky
8. Alex Graves
9. J. Urgen Schmidhuber
10. Ross B. Girshick

Papers from Philippe Beaudoin's perspective

Ordered by how strongly the researchers Philippe Beaudoin 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. 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. Learning Multiple Layers of Features from Tiny Images
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Independently Controllable Factors (2017) — 71 citations
• A deep learning framework for neuroscience (2019) — 1,016 citations
• Neural Production Systems (2021) — 94 citations
• Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems (2020) — 75 citations
• Disentangling the independently controllable factors of variation by interacting with the world (2018) — 69 citations