| 2008 |
|---|
| 9 | EE | Jo-Anne Ting,
Aaron D'Souza,
Sethu Vijayakumar,
Stefan Schaal:
A Bayesian approach to empirical local linearization for robotics.
ICRA 2008: 2860-2865 |
| 8 | EE | Jo-Anne Ting,
Mrinal Kalakrishnan,
Sethu Vijayakumar,
Stefan Schaal:
Bayesian Kernel Shaping for Learning Control.
NIPS 2008: 1673-1680 |
| 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,
Evangelos Theodorou,
Stefan Schaal:
Learning an Outlier-Robust Kalman Filter.
ECML 2007: 748-756 |
| 5 | EE | Jo-Anne Ting,
Aaron D'Souza,
Stefan Schaal:
Automatic Outlier Detection: A Bayesian Approach.
ICRA 2007: 2489-2494 |
| 4 | EE | Jo-Anne Ting,
Evangelos Theodorou,
Stefan Schaal:
A Kalman filter for robust outlier detection.
IROS 2007: 1514-1519 |
| 2006 |
|---|
| 3 | EE | Jo-Anne Ting,
Aaron D'Souza,
Stefan Schaal:
Bayesian regression with input noise for high dimensional data.
ICML 2006: 937-944 |
| 2 | EE | Jo-Anne Ting,
Michael Mistry,
Jan Peters,
Stefan Schaal,
Jun Nakanishi:
A Bayesian Approach to Nonlinear Parameter Identification for Rigid Body Dynamics.
Robotics: Science and Systems 2006 |
| 2005 |
|---|
| 1 | 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 |
