Matteo Leonetti

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Reinforcement Learning — 46 citations into it
• Meta & Continual Learning — 10 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Control and Systems Engineering — 8 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Matteo Leonetti trusts overall

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

1. Richard S. Sutton
2. Matthew E. Taylor
3. Peter Stone
4. Andrew Barto
5. G. Tesauro
6. J. Urgen Schmidhuber
7. W. B. Knox
8. Stefan Schaal
9. Geoffrey E. Hinton
10. Yoshua Bengio

Who trusts Matteo Leonetti overall

1. Sanmit Narvekar
2. Pascal Klink

Papers from Matteo Leonetti's perspective

Ordered by how strongly the researchers Matteo Leonetti 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. Reinforcement Learning: An Introduction
4. Human-level control through deep reinforcement learning
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. GENERATIVE ADVERSARIAL NETS
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey (2020) — 748 citations
• Source Task Creation for Curriculum Learning (2016) — 130 citations