Thomas Hellström

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Safety, Robustness & Interpretability — 20 citations into it
• Natural Language Processing — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it

Whom Thomas Hellström trusts overall

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

1. Hila Gonen
2. Nuno Vasconcelos
3. Svetlana Kiritchenko
4. Yoav Goldberg
5. Anthony W. Flores
6. Marc-Etienne Brunet
7. Robert Geirhos
8. Geoffrey E. Hinton
9. Tomas Mikolov
10. Kate Crawford

Who trusts Thomas Hellström overall

1. Reva Schwartz
2. Apostol T. Vassilev
3. Ryan Shaun Joazeiro de Baker

Papers from Thomas Hellström's perspective

Ordered by how strongly the researchers Thomas Hellström 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Going deeper with convolutions

Their papers

• Bias in machine learning - what is it good for? (2020) — 88 citations
• Development of a sweet pepper harvesting robot (2020) — 386 citations