Matthew Scicluna

2018

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 Matthew Scicluna's perspective

Ordered by how strongly the researchers Matthew Scicluna 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Understanding the difficulty of training deep feedforward neural networks
4. Understanding deep learning requires rethinking generalization
5. Wide Residual Networks
6. Deep Learning
7. Learning long-term dependencies with gradient descent is difficult
8. ImageNet classification with deep convolutional neural networks
9. Gradient-based learning applied to document recognition
10. On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Their papers

• A Modern Take on the Bias-Variance Tradeoff in Neural Networks (2018) — 186 citations