Harjatin Singh Baweja

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it; #31,609 of 35,345 by trust here, #33,294 by citations
• Reinforcement Learning — 46 citations into it
• Control and Systems Engineering — 26 citations into it; #7,315 of 8,257 by trust here, #7,501 by citations
• Computer Vision and Pattern Recognition — 24 citations into it
• Robotics & Control — 17 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Aerospace Engineering — 5 citations into it

Whom Harjatin Singh Baweja trusts overall

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

1. Richard S. Sutton
2. Diederik P. Kingma
3. Sergey Levine
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. Yann LeCun
9. Jimmy Ba
10. Chelsea Finn

Who trusts Harjatin Singh Baweja overall

1. Yu Zhang
2. Benjamin Eysenbach
3. Lucio M. Dery
4. Youngmin Oh

Papers from Harjatin Singh Baweja's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Reinforcement Learning without Ground-Truth State (2019) — 27 citations
• Adaptive Auxiliary Task Weighting for Reinforcement Learning (2019) — 133 citations