Mikel Bober-Irizar

2018

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

Whom Mikel Bober-Irizar trusts overall

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

1. David R Ha
2. Charles M. Bishop
3. Kaiming He
4. J. Urgen Schmidhuber
5. Diederik P. Kingma
6. Han Xiao
7. Geoffrey E. Hinton

Who trusts Mikel Bober-Irizar overall

1. Javier Antorán Cabiscol
2. Arild Nøkland
3. Timothée Lesort
4. Xingchao Peng
5. Noel Loo
6. Sairaam Venkatraman

Papers from Mikel Bober-Irizar's perspective

Ordered by how strongly the researchers Mikel Bober-Irizar 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. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Deep Learning for Classical Japanese Literature (2018) — 864 citations