Seyed Sajad Mousavi

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 15 citations into it
• Artificial Intelligence — 9 citations into it

Whom Seyed Sajad Mousavi trusts overall

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

1. Volodymyr Mnih
2. Longxin Lin
3. Diederik P. Kingma
4. Mohit Sewak
5. van der D David Pol
6. Andrew Barto
7. Yann LeCun
8. Richard S. Sutton
9. Sascha Lange
10. Geoffrey E. Hinton

Who trusts Seyed Sajad Mousavi overall

1. Ammar Haydari
2. Hua Wei
3. Yasin Yilmaz
4. Guanjie Zheng

Papers from Seyed Sajad Mousavi's perspective

Ordered by how strongly the researchers Seyed Sajad Mousavi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning (2017) — 348 citations