Jules Pondard

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Reinforcement Learning — 20 citations into it

Whom Jules Pondard trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. Diederik P. Kingma
4. Doina Precup
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Peter W. Glynn
8. Peter S. Dayan
9. Yann LeCun
10. Jimmy Ba

Papers from Jules Pondard's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Independently Controllable Factors (2017) — 71 citations
• Disentangling the independently controllable factors of variation by interacting with the world (2018) — 69 citations