Laura N. Driscoll

Cognitive Neuroscience · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 28 citations into it
• Artificial Intelligence — 20 citations into it
• Cellular and Molecular Neuroscience — 13 citations into it
• Electrical and Electronic Engineering — 8 citations into it
• Optimization & Training — 5 citations into it

Whom Laura N. Driscoll trusts overall

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

1. Christopher D. Harvey
2. Rafael Yuste
3. David Sussillo
4. Jerome H. Friedman
5. Mikhail A. Lebedev
6. James Martens
7. Trevor J. Hastie
8. Gido M. van de Ven
9. David W. Tank
10. Geoffrey E. Hinton

Who trusts Laura N. Driscoll overall

1. Ta-Chu Kao

Papers from Laura N. Driscoll's perspective

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

Their papers

• Organizing recurrent network dynamics by task-computation to enable continual learning (2020) — 98 citations
• Dynamic Reorganization of Neuronal Activity Patterns in Parietal Cortex. (2017) — 399 citations