Prabhat Nagarajan

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 32 citations into it; #1,839 of 2,242 by trust here, #1,609 by citations
• Artificial Intelligence — 23 citations into it; #27,227 of 35,345 by trust here, #19,018 by citations
• Control and Systems Engineering — 9 citations into it; #7,107 of 8,257 by trust here, #2,890 by citations
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Prabhat Nagarajan trusts overall

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

1. Diederik P. Kingma
2. Martin L. Puterman
3. Pieter Abbeel
4. Faraz Torabi
5. Sergey Levine
6. Geoffrey E. Hinton
7. Andrew Y. Ng
8. John Schulman
9. E. Todorov
10. Individualized Treat

Who trusts Prabhat Nagarajan overall

1. Daniel S. Brown
2. Saurabh Arora

Papers from Prabhat Nagarajan's perspective

Ordered by how strongly the researchers Prabhat Nagarajan 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. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. GENERATIVE ADVERSARIAL NETS
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Human-level control through deep reinforcement learning
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations (2019) — 425 citations