Robert D. Mullins

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 119 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 87 citations into it
• Computer Vision and Pattern Recognition — 64 citations into it
• Model Architectures — 24 citations into it
• Natural Language Processing — 13 citations into it
• Molecular Biology — 8 citations into it

Whom Robert D. Mullins trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Karen Simonyan
6. Yoshua Bengio
7. Ilya Sutskever
8. Yann LeCun
9. X. Zhang
10. Ross B. Girshick

Papers from Robert D. Mullins's perspective

Ordered by how strongly the researchers Robert D. Mullins 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Dynamic Channel Pruning: Feature Boosting and Suppression (2018) — 348 citations
• Sponge Examples: Energy-Latency Attacks on Neural Networks (2020) — 192 citations
• Probabilistic Dual Network Architecture Search on Graphs (2020) — 27 citations