Sebastian Lopez-Cot

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Reinforcement Learning — 42 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it

Whom Sebastian Lopez-Cot trusts overall

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

1. Richard S. Sutton
2. Geoffrey E. Hinton
3. J. Urgen Schmidhuber
4. Yoshua Bengio

Papers from Sebastian Lopez-Cot's perspective

Ordered by how strongly the researchers Sebastian Lopez-Cot 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. Human-level control through deep reinforcement learning
4. Asynchronous Methods for Deep Reinforcement Learning
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Gradient-based learning applied to document recognition
7. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Learning Hierarchical Teaching Policies for Cooperative Agents (2019) — 33 citations
• A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning (2020) — 69 citations