David Donahue

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 191 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Natural Language Processing — 29 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Generative Models — 15 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom David Donahue trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Sepp Hochreiter
5. Alex Krizhevsky
6. Ilya Sutskever
7. Kaiming He
8. J. Urgen Schmidhuber
9. Jimmy Ba
10. Yann LeCun

Papers from David Donahue's perspective

Ordered by how strongly the researchers David Donahue 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Adversarial Decomposition of Text Representation (2018) — 47 citations
• Adversarial Text Generation Without Reinforcement Learning (2018) — 29 citations