Jonathan Lomond
Artificial Intelligence · 2020
A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 17 citations into it
- Scaling & Learning Theory — 15 citations into it
- Statistics and Probability — 12 citations into it
- Computational Mechanics — 9 citations into it
- Optimization & Training — 8 citations into it
- Statistical Learning Theory — 7 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
Whom Jonathan Lomond trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- Trevor J. Hastie
- Jerome H. Friedman
- E.J. Candes
- Mikhail Belkin
- Hui Zou
- Ali Rahimi
- B. Recht
- Tengyuan Liang
- Scott Shaobing Chen
Papers from Jonathan Lomond's perspective
Ordered by how strongly the researchers Jonathan Lomond trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Regression Shrinkage and Selection via the Lasso
- Dropout: a simple way to prevent neural networks from overfitting
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images