Leonardo Banh

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 67 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Generative Models — 15 citations into it
• Health Informatics — 14 citations into it
• Safety Research — 14 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Sociology and Political Science — 10 citations into it
• Computer Graphics and Computer-Aided Design — 6 citations into it

Whom Leonardo Banh trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. Alex Krizhevsky
6. Jonathan Ho
7. Kaiming He
8. Ilya Sutskever
9. Ashish Vaswani
10. Lars Ruthotto

Papers from Leonardo Banh's perspective

Ordered by how strongly the researchers Leonardo Banh 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Generative artificial intelligence (2023) — 334 citations