Leopold Aschenbrenner

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it

Whom Leopold Aschenbrenner trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He

Papers from Leopold Aschenbrenner's perspective

Ordered by how strongly the researchers Leopold Aschenbrenner 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. ImageNet Large Scale Visual Recognition Challenge
4. Dropout: a simple way to prevent neural networks from overfitting
5. Distilling the Knowledge in a Neural Network (arXiv.org)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Language Models are Few-Shot Learners (Neural Information Processing Systems)

Their papers

• Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision (2023) — 504 citations