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Aaron D'Souza
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2010 – 2019
- 2011
- [j5]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Bayesian robot system identification with input and output noise. Neural Networks 24(1): 99-108 (2011) - 2010
- [j4]Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
Efficient Learning and Feature Selection in High-Dimensional Regression. Neural Comput. 22(4): 831-886 (2010)
2000 – 2009
- 2008
- [j3]Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka, Donna L. Hoffman, Shinji Kakei, Lauren Sergio, John Kalaska, Mitsuo Kawato, Peter Strick, Stefan Schaal:
Variational Bayesian least squares: An application to brain-machine interface data. Neural Networks 21(8): 1112-1131 (2008) - [c6]Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
A Bayesian approach to empirical local linearization for robotics. ICRA 2008: 2860-2865 - 2007
- [c5]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Automatic Outlier Detection: A Bayesian Approach. ICRA 2007: 2489-2494 - 2006
- [c4]Jo-Anne Ting, Aaron D'Souza, Stefan Schaal:
Bayesian regression with input noise for high dimensional data. ICML 2006: 937-944 - 2005
- [j2]Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal:
Incremental Online Learning in High Dimensions. Neural Comput. 17(12): 2602-2634 (2005) - [c3]Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka, Donna L. Hoffman, Lauren Sergio, Shinji Kakei, John Kalaska, Mitsuo Kawato, Peter Strick, Stefan Schaal:
Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares. NIPS 2005: 1361-1368 - 2004
- [c2]Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
The Bayesian backfitting relevance vector machine. ICML 2004 - 2002
- [j1]Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata, Jörg Conradt, Stefan Schaal:
Statistical Learning for Humanoid Robots. Auton. Robots 12(1): 55-69 (2002) - 2001
- [c1]Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal:
Learning inverse kinematics. IROS 2001: 298-303
Coauthor Index
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