Quentin Vanhaelen

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 11 citations into it
• Artificial Intelligence — 9 citations into it

Whom Quentin Vanhaelen trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Radford M. Neal
5. Ilya Sutskever
6. Yoshua Bengio
7. Individualized Treat

Papers from Quentin Vanhaelen's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. GENERATIVE ADVERSARIAL NETS
5. Dropout: a simple way to prevent neural networks from overfitting
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology (2016) — 323 citations
• Integrated deep learned transcriptomic and structure-based predictor of clinical trials outcomes (2016) — 33 citations