Vincent Lenders

Artificial Intelligence · 2014–2017

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 — 8 citations into it

Whom Vincent Lenders trusts overall

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

1. Diederik P. Kingma
2. Tim O'Shea

Papers from Vincent Lenders's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Learning
4. Visualizing Data using t-SNE
5. ImageNet classification with deep convolutional neural networks
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors (2017) — 780 citations
• Bringing up OpenSky: A large-scale ADS-B sensor network for research (2014) — 475 citations