Guillaume Quispe

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 54 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Natural Language Processing — 30 citations into it
• Reinforcement Learning — 23 citations into it
• Multimodal Learning — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Guillaume Quispe trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Ronald J. Williams
4. Yoshua Bengio
5. Kaiming He
6. Richard S. Sutton
7. Alex Krizhevsky
8. Ilya Sutskever
9. Yann LeCun
10. Ross B. Girshick

Papers from Guillaume Quispe's perspective

Ordered by how strongly the researchers Guillaume Quispe 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Learning Natural Language Generation with Truncated Reinforcement Learning (2022) — 9 citations