Hootan Nakhost

Artificial Intelligence · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it
• Natural Language Processing — 25 citations into it

Whom Hootan Nakhost trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Jason Wei
6. Ilya Sutskever
7. Yann LeCun
8. Kaiming He
9. Dzmitry Bahdanau
10. Oriol Vinyals

Papers from Hootan Nakhost's perspective

Ordered by how strongly the researchers Hootan Nakhost 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Distilling the Knowledge in a Neural Network (arXiv.org)
10. Gradient-based learning applied to document recognition

Their papers

• Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes (2023) — 990 citations
• SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (2024) — 96 citations