Raoul-Gabriel Urma

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Information Systems — 11 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Raoul-Gabriel Urma trusts overall

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

1. J. Ross Quinlan
2. Chelsea Finn
3. Randal S. Olson
4. Paroma Varma
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Yoshua Bengio
8. Diederik P. Kingma
9. Haifeng Jin
10. Curtis G. Northcutt

Papers from Raoul-Gabriel Urma's perspective

Ordered by how strongly the researchers Raoul-Gabriel Urma 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Challenges in Deploying Machine Learning: A Survey of Case Studies (2020) — 636 citations