Alice Martin

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 129 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it
• Computer Vision and Pattern Recognition — 47 citations into it
• Natural Language Processing — 30 citations into it
• Reinforcement Learning — 25 citations into it
• Probabilistic & Bayesian Methods — 18 citations into it
• Optimization & Training — 13 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Evaluation & Benchmarks — 11 citations into it

Whom Alice Martin trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Ronald J. Williams
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Richard S. Sutton
10. Radford M. Neal

Who trusts Alice Martin overall

1. G. Qian
2. Rajkumar Ramamurthy

Papers from Alice Martin's perspective

Ordered by how strongly the researchers Alice Martin 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Learning Natural Language Generation with Truncated Reinforcement Learning (2022) — 9 citations
• On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation (2020) — 37 citations