Jordi Torres

Artificial Intelligence · with Giró-i-Nieto · 2016–2020

A researcher in the Science corpus: 6 papers; trusts 571 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 134 citations into it
• Computer Vision and Pattern Recognition — 129 citations into it
• Model Architectures — 46 citations into it
• Reinforcement Learning — 46 citations into it
• Natural Language Processing — 21 citations into it
• Optimization & Training — 17 citations into it
• Management Science and Operations Research — 12 citations into it

Whom Jordi Torres trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ross B. Girshick
7. Ilya Sutskever
8. Alex Graves
9. Yann LeCun
10. Karen Simonyan

Papers from Jordi Torres's perspective

Ordered by how strongly the researchers Jordi Torres 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. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks (2017) — 236 citations
• Recurrent Neural Networks for Semantic Instance Segmentation (2017) — 65 citations
• SalGAN: Visual Saliency Prediction with Generative Adversarial Networks (2017) — 432 citations
• Hierarchical Object Detection with Deep Reinforcement Learning (2016) — 115 citations
• Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills (2020) — 186 citations
• How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language (2020) — 353 citations