Joël Kuiper
Artificial Intelligence · 2015–2018
A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 11 citations into it
Whom Joël Kuiper trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Joël Kuiper's perspective
Ordered by how strongly the researchers Joël Kuiper trusts endorse each paper. Same corpus, a different order for every researcher.
- Dropout: a simple way to prevent neural networks from overfitting
- GloVe: Global Vectors for Word Representation
- ImageNet classification with deep convolutional neural networks
- Bagging Predictors
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Text Categorization with Support Vector Machines: Learning with Many Relevant Features
- Learning Multiple Layers of Features from Tiny Images