Eric D. Ragan

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 249 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 104 citations into it; #13,747 of 35,345 by trust here, #19,018 by citations
• Safety, Robustness & Interpretability — 64 citations into it
• Computer Vision and Pattern Recognition — 57 citations into it; #8,959 of 21,575 by trust here, #12,689 by citations
• Human-Computer Interaction — 24 citations into it
• Safety Research — 22 citations into it
• Sociology and Political Science — 18 citations into it
• Information Systems and Management — 15 citations into it; #976 of 3,842 by trust here, #2,689 by citations
• Information Systems — 14 citations into it

Whom Eric D. Ragan trusts overall

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

1. Geoffrey E. Hinton
2. Karen Simonyan
3. L. V. D. van der Maaten
4. Finale Doshi-Velez
5. Alex Krizhevsky
6. Christian Szegedy
7. Yoshua Bengio
8. Josua Krause
9. Andrew Zisserman
10. Diederik P. Kingma

Who trusts Eric D. Ragan overall

1. Laura Rieger
2. Lars Kai Hansen
3. Amina Adadi
4. Sina Mohseni
5. Khansa Rasheed
6. Mohammed Berrada

Papers from Eric D. Ragan's perspective

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

Their papers

• Impact assessment of reinforced learning methods on construction workers' fall risk behavior using virtual reality (2019) — 187 citations
• A Human-Grounded Evaluation Benchmark for Local Explanations of Machine Learning (2018) — 63 citations
• A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems (2018) — 808 citations