Robert Gens

Artificial Intelligence · 2012–2014

A researcher in the Science corpus: 3 papers; trusts 92 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Signal Processing — 7 citations into it
• Model Architectures — 6 citations into it; #524 of 2,278 by trust here, #1,124 by citations

Whom Robert Gens trusts overall

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

1. Adam Coates
2. Yoshua Bengio
3. Yann LeCun
4. Andrew Y. Ng
5. Adnan Darwiche
6. Geoffrey E. Hinton
7. Alex Krizhevsky
8. Aapo Hyvärinen
9. Pedro F. Felzenszwalb
10. Emanuel Parzen

Who trusts Robert Gens overall

1. Taco Cohen
2. Li Deng
3. Siamak Ravanbakhsh
4. Geoffrey E. Hinton
5. Ping Luo
6. Tsung-Yu Lin
7. David W. Romero
8. James Martens
9. Diego Marcos
10. David Kristjanson Duvenaud

Papers from Robert Gens's perspective

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

Their papers

• Deep Symmetry Networks (2014) — 280 citations
• Learning the Structure of Sum-Product Networks (2013) — 302 citations
• Discriminative Learning of Sum-Product Networks (2012) — 197 citations