Florian Graf

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 79 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it
• Computer Vision and Pattern Recognition — 35 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 13 citations into it
• Optimization & Training — 12 citations into it
• Statistical Learning Theory — 10 citations into it

Whom Florian Graf trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. X. Zhang
5. Shaoqing Ren
6. Yann LeCun
7. Yoshua Bengio
8. Tong Zhang
9. Peter L. Bartlett
10. Ilya Sutskever

Who trusts Florian Graf overall

1. Yibo Yang

Papers from Florian Graf's perspective

Ordered by how strongly the researchers Florian Graf 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• On Measuring Excess Capacity in Neural Networks (2022) — 13 citations
• Dissecting Supervised Constrastive Learning (2021) — 74 citations