Damian Borth

Artificial Intelligence · with Kostadinov · 2021

A researcher in the Science corpus: 1 paper; trusts 73 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Representation & Self-Supervised Learning — 10 citations into it

Whom Damian Borth trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Alex Krizhevsky
6. Yann LeCun
7. Matthew D. Zeiler
8. Radford M. Neal
9. Jimmy Ba
10. Ilya Sutskever

Papers from Damian Borth's perspective

Ordered by how strongly the researchers Damian Borth 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction (2021) — 63 citations