| 2008 |
|---|
| 8 | EE | Jo-Anne Ting,
Aaron D'Souza,
Sethu Vijayakumar,
Stefan Schaal:
A Bayesian approach to empirical local linearization for robotics.
ICRA 2008: 2860-2865 |
| 7 | EE | 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) |
| 2007 |
|---|
| 6 | EE | Jo-Anne Ting,
Aaron D'Souza,
Stefan Schaal:
Automatic Outlier Detection: A Bayesian Approach.
ICRA 2007: 2489-2494 |
| 2006 |
|---|
| 5 | EE | Jo-Anne Ting,
Aaron D'Souza,
Stefan Schaal:
Bayesian regression with input noise for high dimensional data.
ICML 2006: 937-944 |
| 2005 |
|---|
| 4 | EE | 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 |
| 3 | EE | Sethu Vijayakumar,
Aaron D'Souza,
Stefan Schaal:
Incremental Online Learning in High Dimensions.
Neural Computation 17(12): 2602-2634 (2005) |
| 2004 |
|---|
| 2 | EE | Aaron D'Souza,
Sethu Vijayakumar,
Stefan Schaal:
The Bayesian backfitting relevance vector machine.
ICML 2004 |
| 2002 |
|---|
| 1 | | Sethu Vijayakumar,
Aaron D'Souza,
Tomohiro Shibata,
Jörg Conradt,
Stefan Schaal:
Statistical Learning for Humanoid Robots.
Auton. Robots 12(1): 55-69 (2002) |
