Abhishek Naik

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 27 citations into it
• Artificial Intelligence — 24 citations into it
• Control and Systems Engineering — 9 citations into it

Whom Abhishek Naik trusts overall

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

1. Pieter Abbeel
2. Andrew Y. Ng
3. Richard S. Sutton
4. Diederik P. Kingma
5. Stefan Schaal
6. Stéphane Ross
7. Sergey Levine
8. Geoffrey E. Hinton
9. E. Todorov
10. Individualized Treat

Papers from Abhishek Naik's perspective

Ordered by how strongly the researchers Abhishek Naik 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. GENERATIVE ADVERSARIAL NETS
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Reinforcement Learning: An Introduction
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• RAIL: Risk-Averse Imitation Learning (2017) — 21 citations