Iyad Rahwan
Artificial Intelligence · 2003–2023
A researcher in the Science corpus: 16 papers; trusts 96 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 134 citations into it; #32,045 of 35,345 by trust here, #13,544 by citations
- Sociology and Political Science — 55 citations into it; #4,860 of 22,756 by trust here, #8,438 by citations
- Computer Vision and Pattern Recognition — 50 citations into it
- Natural Language Processing — 43 citations into it; #2,686 of 5,688 by trust here, #2,263 by citations
- Safety, Robustness & Interpretability — 28 citations into it
- AI Ethics, Fairness & Society — 27 citations into it; #467 of 494 by trust here, #141 by citations
- Management Science and Operations Research — 26 citations into it
- Reinforcement Learning — 26 citations into it
Whom Iyad Rahwan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Joshua D. Greene
- Jean‐François Bonnefon
- Eytan Bakshy
- Yoshua Bengio
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Tomas Mikolov
- Sarit Kraus
- Latanya Sweeney
Who trusts Iyad Rahwan overall
- Davinder Kaur
- Stefan Larsson
- Jonathan Stray
- Maranke Wieringa
- Suleyman Uslu
- Fredrik Heintz
- Bernd W. Wirtz
- Kaley J. Rittichier
- Deven Santosh Shah
- Jessica Morley
Papers from Iyad Rahwan's perspective
Ordered by how strongly the researchers Iyad Rahwan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Evaluating Style Transfer for Text (2019) — 123 citations
- Human detection of machine-manipulated media (2019) — 25 citations
- Cooperating with machines (2017) — 251 citations
- The social dilemma of autonomous vehicles (2015) — 1,338 citations
- Toward understanding the impact of artificial intelligence on labor (2019) — 615 citations
- Society-in-the-loop: programming the algorithmic social contract (2017) — 458 citations
- The Moral Machine experiment (2018) — 1,563 citations
- Information verification during natural disasters (2013) — 38 citations
- Machine culture (2023)
- Machine behaviour (2019) — 1,247 citations
- The Trolley, the Bull Bar, and Why Engineers Should Care About the Ethics of Autonomous Cars (2019) — 73 citations
- Darling or Babygirl ? Investigating Stylistic Bias in Sentiment Analysis (2018)
- Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm (2017) — 813 citations
- Autonomous Vehicles Need Experimental Ethics: Are We Ready for Utilitarian Cars? (2015) — 105 citations
- Towards an argument interchange format (2006) — 405 citations
- Argumentation-based negotiation (2003) — 664 citations