Felix Hohne

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Graph Learning — 18 citations into it

Whom Felix Hohne trusts overall

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

1. Diederik P. Kingma
2. Jure Leskovec
3. Sergey Ioffe
4. Lubos Takac
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Jimmy Ba
8. Alex Krizhevsky
9. Christian Szegedy
10. William L. Hamilton

Papers from Felix Hohne's perspective

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

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

Their papers

• Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods (2021) — 492 citations