Michael Foster

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 6 citations into it

Whom Michael Foster trusts overall

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

1. Andrew L. Maas

Papers from Michael Foster's perspective

Ordered by how strongly the researchers Michael Foster 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Going deeper with convolutions
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Dropout: a simple way to prevent neural networks from overfitting
6. ImageNet classification with deep convolutional neural networks
7. Gradient-based learning applied to document recognition
8. Rectifier Nonlinearities Improve Neural Network Acoustic Models
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Deep Convolutional Neural Networks for Raman Spectrum Recognition: A Unified Solution (2017) — 367 citations