Thomas A. Hogan

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Thomas A. Hogan trusts overall

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

1. Nicholas Carlini
2. Ian J. Goodfellow
3. Nicolas Papernot
4. Pin-Yu Chen
5. Christian Szegedy
6. Minhao Cheng
7. David A. Wagner
8. Geoffrey E. Hinton
9. Alex Krizhevsky
10. Patrick Drew McDaniel

Papers from Thomas A. Hogan's perspective

Ordered by how strongly the researchers Thomas A. Hogan 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Intriguing properties of neural networks

Their papers

• Universal Hard-label Black-Box Perturbations: Breaking Security-Through-Obscurity Defenses (2018) — 4 citations
• Universal Decision-Based Black-Box Perturbations: Breaking Security-Through-Obscurity Defenses (2018) — 11 citations