Ken Caluwaerts

Reinforcement Learning · 2014–2019

A researcher in the Science corpus: 5 papers; trusts 23 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 58 citations into it
• Artificial Intelligence — 55 citations into it; #29,277 of 35,345 by trust here, #19,018 by citations
• Biomedical Engineering — 38 citations into it; #10,323 of 10,734 by trust here, #7,109 by citations
• Computer Vision and Pattern Recognition — 22 citations into it; #20,837 of 21,575 by trust here, #20,271 by citations
• Aerospace Engineering — 11 citations into it
• Optimization & Training — 9 citations into it

Whom Ken Caluwaerts trusts overall

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

1. Sergey Levine
2. John Schulman
3. Richard S. Sutton
4. Pieter Abbeel
5. Geoffrey E. Hinton
6. Chelsea Finn
7. Diederik P. Kingma
8. Sepp Hochreiter
9. Yoshua Bengio
10. Jan Peters

Who trusts Ken Caluwaerts overall

1. Julian Ibarz
2. Jie Tan
3. Sehoon Ha
4. Jemin Hwangbo
5. Jixiang Guo
6. Khimya Khetarpal

Papers from Ken Caluwaerts's perspective

Ordered by how strongly the researchers Ken Caluwaerts 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Policies Modulating Trajectory Generators (2018) — 151 citations
• Data Efficient Reinforcement Learning for Legged Robots (2019) — 169 citations
• NoRML: No-Reward Meta Learning (2019) — 29 citations
• Deep reinforcement learning for tensegrity robot locomotion (2016) — 106 citations
• Design and control of compliant tensegrity robots through simulation and hardware validation (2014) — 294 citations