Martin Pawelczyk

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 Martin Pawelczyk 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. Jerome H. Friedman
10. Alex Graves

Papers from Martin Pawelczyk's perspective

Ordered by how strongly the researchers Martin Pawelczyk 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Gradient-based learning applied to document recognition
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