Max Horn

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Model Architectures — 14 citations into it

Whom Max Horn trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Kaiming He
4. Ashish Vaswani
5. Geoffrey E. Hinton
6. Ilya Sutskever
7. Andrew Zisserman
8. Yann LeCun
9. Yoshua Bengio
10. Diederik P. Kingma

Papers from Max Horn's perspective

Ordered by how strongly the researchers Max Horn 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. Attention is All you Need (Neural Information Processing Systems)
4. Gradient-based learning applied to document recognition
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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Translational Equivariance in Kernelizable Attention (2021) — 8 citations
• Early prediction of circulatory failure in the intensive care unit using machine learning (2020) — 430 citations