Nathalie Bradley-Schmieg

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 120 citations into it
• Reinforcement Learning — 61 citations into it

Whom Nathalie Bradley-Schmieg trusts overall

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

1. J. Urgen Schmidhuber

Papers from Nathalie Bradley-Schmieg's perspective

Ordered by how strongly the researchers Nathalie Bradley-Schmieg 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. Long Short-Term Memory
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Human-level control through deep reinforcement learning
8. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
9. Gradient-based learning applied to document recognition
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Open-Ended Learning Leads to Generally Capable Agents (2021) — 230 citations
• Human-Timescale Adaptation in an Open-Ended Task Space (2023) — 163 citations