Alexander J. Geers

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it

Whom Alexander J. Geers trusts overall

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

1. M. Stone
2. Yann LeCun
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Ilya Sutskever
7. Ming-Ming Cheng
8. L. Eon Bottou

Papers from Alexander J. Geers's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• An on-chip photonic deep neural network for image classification (2021) — 603 citations