Graham F. Healy

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 461 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 87 citations into it
• Artificial Intelligence — 78 citations into it
• Representation & Self-Supervised Learning — 61 citations into it
• Generative Models — 22 citations into it
• Signal Processing — 19 citations into it
• Natural Language Processing — 16 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Graph Learning — 7 citations into it

Whom Graham F. Healy trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Andrew Zisserman
9. Ross B. Girshick
10. Sepp Hochreiter

Who trusts Graham F. Healy overall

1. Gabriel Ilharco

Papers from Graham F. Healy's perspective

Ordered by how strongly the researchers Graham F. Healy 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Contrastive Representation Learning: A Framework and Review (2020) — 957 citations
• Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative adversarial networks (2019) — 13 citations