Alison Smith-Renner

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 87 citations into it
• Safety, Robustness & Interpretability — 47 citations into it
• Safety Research — 34 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it

Whom Alison Smith-Renner trusts overall

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

1. Todd Kulesza
2. Marco Tulio Ribeiro
3. Jacob O. Wobbrock
4. William Saunders
5. Saleema Amershi
6. Simone Stumpf
7. Ming Yin
8. Margaret M. Burnett
9. Ben Green
10. Geoffrey E. Hinton

Who trusts Alison Smith-Renner overall

1. Vivian Lai
2. Q. Liao

Papers from Alison Smith-Renner's perspective

Ordered by how strongly the researchers Alison Smith-Renner trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies (2021) — 249 citations
• No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML (2020) — 172 citations