Layne Price

2016

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Layne Price's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Learning Deep Architectures for AI
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Visualizing Higher-Layer Features of a Deep Network
8. Random Features for Large-Scale Kernel Machines
9. Deep Learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Estimating Cosmological Parameters from the Dark Matter Distribution (2016) — 83 citations