Amanda Prorok

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 24 citations into it
• Artificial Intelligence — 22 citations into it
• Reinforcement Learning — 8 citations into it
• Aerospace Engineering — 7 citations into it
• Computer Networks and Communications — 7 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Amanda Prorok trusts overall

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

1. David Silver
2. Jur van den Berg
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Geoffrey E. Hinton

Papers from Amanda Prorok's perspective

Ordered by how strongly the researchers Amanda Prorok trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Human-level control through deep reinforcement learning
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Mobile Robot Path Planning in Dynamic Environments Through Globally Guided Reinforcement Learning (2020) — 335 citations
• Graph Neural Networks for Decentralized Multi-Robot Path Planning (2019) — 315 citations