Hagen Wierstorf

Representation & Self-Supervised Learning · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 9 citations into it
• Signal Processing — 9 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Hagen Wierstorf trusts overall

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

1. Karol J. Piczak
2. Geoffrey E. Hinton

Papers from Hagen Wierstorf's perspective

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

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. A Simple Framework for Contrastive Learning of Visual Representations (International Conference on Machine Learning)
8. Long Short-Term Memory
9. Visualizing Data using t-SNE
10. ImageNet: A large-scale hierarchical image database

Their papers

• Dawn of the Transformer Era in Speech Emotion Recognition: Closing the Valence Gap (2022) — 492 citations