Ashutosh Kumar Jha

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 15 citations into it
• Electrical and Electronic Engineering — 5 citations into it

Whom Ashutosh Kumar Jha trusts overall

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

1. Richard S. Sutton
2. Volodymyr Mnih
3. Burr Settles
4. Yann LeCun
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Peter Auer
8. Aravind S. Lakshminarayanan
9. Jimmy Ba
10. Emilio Parisotto

Who trusts Ashutosh Kumar Jha overall

1. Michael Crawshaw
2. Matthew Riemer
3. Miao Liu
4. Han-Jia Ye
5. Wei-Lun Chao
6. Yu Zhang

Papers from Ashutosh Kumar Jha's perspective

Ordered by how strongly the researchers Ashutosh Kumar Jha 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. Gradient-based learning applied to document 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Learning to Multi-Task by Active Sampling (2017) — 40 citations