John Alberg

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it
• Model Architectures — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom John Alberg trusts overall

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

1. Zachary Chase Lipton
2. Ilya Sutskever
3. Oriol Vinyals
4. David C. Kale
5. Yoshua Bengio
6. J. Lewellen
7. Geoffrey E. Hinton
8. Dzmitry Bahdanau
9. Kyunghyun Cho
10. Alex Graves

Who trusts John Alberg overall

1. Fuli Feng
2. Xiangnan He

Papers from John Alberg's perspective

Ordered by how strongly the researchers John Alberg trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals (2017) — 50 citations