Robert D. Hawkins

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 75 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 82 citations into it; #31,690 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 55 citations into it; #5,203 of 5,688 by trust here, #4,879 by citations
• Reinforcement Learning — 32 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Multimodal Learning — 8 citations into it
• Language and Linguistics — 5 citations into it

Whom Robert D. Hawkins trusts overall

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

1. Oriol Vinyals
2. Geoffrey E. Hinton
3. Chelsea Finn
4. Yoshua Bengio
5. Diederik P. Kingma
6. Ilya Sutskever
7. Alex Krizhevsky
8. Tomas Mikolov
9. Sergey Levine
10. Noah D. Goodman

Who trusts Robert D. Hawkins overall

1. Daniel Fried
2. Jessy Lin
3. Panos Achlioptas

Papers from Robert D. Hawkins's perspective

Ordered by how strongly the researchers Robert D. Hawkins 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding (2017) — 145 citations
• Learning Rewards from Linguistic Feedback (2020) — 69 citations
• Continual Adaptation for Efficient Machine Communication (2019) — 39 citations