Javier Antorán Cabiscol

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 106 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Safety, Robustness & Interpretability — 19 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Probabilistic & Bayesian Methods — 15 citations into it
• Generative Models — 11 citations into it
• Natural Language Processing — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Javier Antorán Cabiscol trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. Max Welling
6. Alex Graves
7. Alex Krizhevsky
8. Stefan Depeweg
9. Danilo Jimenez Rezende
10. Ian J. Goodfellow

Papers from Javier Antorán Cabiscol's perspective

Ordered by how strongly the researchers Javier Antorán Cabiscol 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Understanding Uncertainty in Bayesian Neural Networks (2019)