Humberto Nicolás Castejón Martínez

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 8 citations into it; #1,503 of 2,242 by trust here, #2,036 by citations
• Artificial Intelligence — 7 citations into it; #21,586 of 35,345 by trust here, #28,481 by citations

Whom Humberto Nicolás Castejón Martínez trusts overall

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

1. Volodymyr Mnih
2. Richard S. Sutton
3. Razvan Pascanu
4. Marc G. Bellemare
5. Ronald J. Williams
6. Koray Kavukcuoglu
7. Yoshua Bengio
8. Alex Graves
9. Geoffrey E. Hinton
10. Mohammad Babaeizadeh

Who trusts Humberto Nicolás Castejón Martínez overall

1. Artyom Y. Sorokin
2. Shangtong Zhang

Papers from Humberto Nicolás Castejón Martínez's perspective

Ordered by how strongly the researchers Humberto Nicolás Castejón Martínez trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Asynchronous Methods for Deep Reinforcement Learning
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Human-level control through deep reinforcement learning
7. Playing Atari with Deep Reinforcement Learning (arXiv.org)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. The Arcade Learning Environment: An Evaluation Platform for General Agents
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Efficient Parallel Methods for Deep Reinforcement Learning (2017) — 119 citations