Duy Nguyen-Tuong
Artificial Intelligence · 2007–2018
A researcher in the Science corpus: 8 papers; trusts 76 researchers and is trusted by 47 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 62 citations into it; #4,786 of 35,345 by trust here, #9,465 by citations
- Control and Systems Engineering — 41 citations into it; #473 of 8,257 by trust here, #858 by citations
- Reinforcement Learning — 27 citations into it; #581 of 2,242 by trust here, #1,371 by citations
- Probabilistic & Bayesian Methods — 21 citations into it; #1,076 of 1,525 by trust here, #809 by citations
- Computer Vision and Pattern Recognition — 20 citations into it
- Optimization & Training — 13 citations into it
- Statistical Learning Theory — 12 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
Whom Duy Nguyen-Tuong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Christopher K. I. Williams
- Stefan Schaal
- Manfred Opper
- Carl E. Rasmussen
- Sethu Vijayakumar
- Richard S. Sutton
- Michael I. Jordan
- Joaquin Quiñonero Candela
- Christopher G. Atkeson
- Jan Peters
Who trusts Duy Nguyen-Tuong overall
- Jan Peters
- Aude Gemma Billard
- Marc Peter Deisenroth
- Le Yang
- Haitao Liu
- Seyed Mohammad Khansari-Zadeh
- Olivier Sigaud
- Konstantinos Chatzilygeroudis
- J. Krichmar
- Joschka Boedecker
Papers from Duy Nguyen-Tuong's perspective
Ordered by how strongly the researchers Duy Nguyen-Tuong trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Model learning for robot control: a survey (2011) — 557 citations
- Model Learning with Local Gaussian Process Regression (2009) — 345 citations
- Using model knowledge for learning inverse dynamics (2010) — 210 citations
- Towards Motor Skill Learning for Robotics (2007) — 40 citations
- Safe Exploration for Active Learning with Gaussian Processes (2015) — 116 citations
- Probabilistic Recurrent State-Space Models (2018) — 149 citations
- Stability of Controllers for Gaussian Process Forward Models (2016) — 37 citations
- Local Gaussian Process Regression for Real Time Online Model Learning (2008) — 280 citations