Elias Stengel-Eskin

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 57 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Multimodal Learning — 15 citations into it
• Large Language Models — 5 citations into it

Whom Elias Stengel-Eskin trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Kaiming He
4. Diederik P. Kingma
5. Jacob Devlin
6. Alex Krizhevsky
7. Ilya Sutskever
8. Tsung-Yi Lin
9. Drew A. Hudson
10. Christopher D. Manning

Papers from Elias Stengel-Eskin's perspective

Ordered by how strongly the researchers Elias Stengel-Eskin trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
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. Gradient-based learning applied to document recognition
9. Microsoft COCO: Common Objects in Context
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Visual Commonsense in Pretrained Unimodal and Multimodal Models (2022) — 45 citations