Kathrin Sessler

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 119 citations into it
• Computer Vision and Pattern Recognition — 54 citations into it
• Generative Models — 20 citations into it
• Large Language Models — 17 citations into it
• Model Architectures — 16 citations into it
• Optimization & Training — 12 citations into it
• Signal Processing — 8 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Kathrin Sessler trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alec Radford
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Kaiming He
8. Yann LeCun
9. Alex Graves
10. Jerome H. Friedman

Who trusts Kathrin Sessler overall

1. Stefan Hegselmann

Papers from Kathrin Sessler's perspective

Ordered by how strongly the researchers Kathrin Sessler 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Language Models are Realistic Tabular Data Generators (2022) — 423 citations
• Deep Neural Networks and Tabular Data: A Survey (2021) — 1,211 citations