Markus Holzleitner

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 95 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Model Architectures — 42 citations into it
• Reinforcement Learning — 27 citations into it

Whom Markus Holzleitner trusts overall

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

1. Geoffrey E. Hinton
2. Sepp Hochreiter
3. Yoshua Bengio
4. Diederik P. Kingma
5. Yann LeCun
6. Alex Graves
7. J. Urgen Schmidhuber
8. Jimmy Ba
9. Alex Krizhevsky
10. Richard S. Sutton

Papers from Markus Holzleitner's perspective

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

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

Their papers

• Hopfield Networks is All You Need (2020) — 701 citations
• History Compression via Language Models in Reinforcement Learning (2022) — 53 citations
• Modern Hopfield Networks and Attention for Immune Repertoire Classification (2020) — 148 citations