Aaron D'Souza

Publication Activity (10 Years)

Years Active: 2001-2011
Publications (10 Years): 0

Publications

Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
Bayesian robot system identification with input and output noise. Neural Networks 24 (1) (2011)
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
Efficient Learning and Feature Selection in High-Dimensional Regression. Neural Comput. 22 (4) (2010)
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
A Bayesian approach to empirical local linearization for robotics. ICRA (2008)
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) (2008)
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
Automatic Outlier Detection: A Bayesian Approach. ICRA (2007)
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
Bayesian regression with input noise for high dimensional data. ICML (2006)
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)
Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal
Incremental Online Learning in High Dimensions. Neural Comput. 17 (12) (2005)
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
The Bayesian backfitting relevance vector machine. ICML (2004)
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata, Jörg Conradt, Stefan Schaal
Statistical Learning for Humanoid Robots. Auton. Robots 12 (1) (2002)
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
Learning inverse kinematics. IROS (2001)