Asim Munawar

Reinforcement Learning · 2017–2018

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

• Reinforcement Learning — 29 citations into it
• Artificial Intelligence — 28 citations into it

Whom Asim Munawar trusts overall

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

1. Matthew D. Zeiler
2. Volodymyr Mnih
3. Diederik P. Kingma
4. Timothy P. Lillicrap
5. John Schulman
6. Geoffrey E. Hinton

Papers from Asim Munawar's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. GENERATIVE ADVERSARIAL NETS
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Asynchronous Methods for Deep Reinforcement Learning
6. Human-level control through deep reinforcement learning
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
10. Trust Region Policy Optimization (International Conference on Machine Learning)

Their papers

• Constrained Exploration and Recovery from Experience Shaping (2018) — 3 citations
• Deep reinforcement learning for high precision assembly tasks (2017) — 300 citations