Andrew D. Trister

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it

Whom Andrew D. Trister trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton

Papers from Andrew D. Trister's perspective

Ordered by how strongly the researchers Andrew D. Trister trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning (2022) — 716 citations
• Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms (2020) — 345 citations
• The mPower study, Parkinson disease mobile data collected using ResearchKit (2016) — 600 citations