Leonard Bereska

Artificial Intelligence · 2024

A researcher in the Science corpus: 1 paper; trusts 74 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it
• Safety, Robustness & Interpretability — 32 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Large Language Models — 14 citations into it
• Natural Language Processing — 12 citations into it

Whom Leonard Bereska trusts overall

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

1. Yonatan Belinkov
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Matthew D. Zeiler
5. Alex Krizhevsky
6. Diederik P. Kingma
7. Ilya Sutskever
8. Barbara Olshausen
9. Yann LeCun
10. Kaiming He

Papers from Leonard Bereska's perspective

Ordered by how strongly the researchers Leonard Bereska 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Mechanistic Interpretability for AI Safety - A Review (2024) — 483 citations