Aaron D'Souza

Most-cited papers

Incremental Online Learning in High Dimensions
S. Vijayakumar, Aaron D'Souza, S. Schaal
2005Neural Computation616 citations Open access
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Learning inverse kinematics
Aaron D'Souza, S. Vijayakumar, S. Schaal
2001Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180)345 citations Open access
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The Bayesian backfitting relevance vector machine
Aaron D'Souza, S. Vijayakumar, Stefan Schaal
2004International Conference on Machine Learning196 citations
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Bayesian Backfitting
Aaron D'Souza, S. Vijayakumar, Stefan Schaal
199875 citations
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Automatic Outlier Detection: A Bayesian Approach
Jo-Anne Ting, Aaron D'Souza, S. Schaal
2007Proceedings 2007 IEEE International Conference on Robotics and Automation54 citations Open access
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Variational Bayesian least squares: An application to brain-machine interface data
Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka +7 more
2008Neural Networks34 citations Open access
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LWPR: A Scalable Method for Incremental Online Learning in High Dimensions
S. Vijayakumar, Aaron D'Souza, S. Schaal
200532 citations
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Bayesian robot system identification with input and output noise
Jo-Anne Ting, Aaron D'Souza, S. Schaal
2011Neural Networks31 citations
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Efficient Learning and Feature Selection in High-Dimensional Regression
Jo-Anne Ting, Aaron D'Souza, S. Vijayakumar, S. Schaal
2010Neural Computation27 citations Open access
Semantic Scholar
A Bayesian approach to empirical local linearization for robotics
Jo-Anne Ting, Aaron D'Souza, S. Vijayakumar, S. Schaal
2008IEEE International Conference on Robotics and Automation20 citations
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An Automated Lab Instructor for Simulated Science Experiments
Aaron D'Souza, J. Rickel, B. Herreros, W. Johnson
200118 citations
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Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
Jo-Anne Ting, Aaron D'Souza, Kenji Yamamoto, Toshinori Yoshioka +7 more
2005Neural Information Processing Systems16 citations
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Bayesian regression with input noise for high dimensional data
Jo-Anne Ting, Aaron D'Souza, S. Schaal
2006International Conference on Machine Learning13 citations
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Are internal models of the entire body learnable
Aaron D'Souza, S. Vijayakumar, S. Schaal
20018 citations
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Using EM To Estimate A Probablity Density With A Mixture Of Gaussians
Aaron D'Souza
20146 citations
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Towards tractable parameter-free statistical learning
S. Schaal, Aaron D'Souza
20045 citations
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Automatic License plate Recognition System
Aaron D'Souza, S. Dalal
20113 citations
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The Bayesian Backtting Relevance Vector Machine
Aaron D'Souza, S. Vijayakumar, S. Schaal
20043 citations
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Active Learning Strategies for Efficient Machine-Learned Interatomic Potentials Across Diverse Material Systems
M. Khan, Aaron D'Souza, V. Choyal
2026arXiv.org2 citations
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Bayesian backfitting for high dimensional regression
Aaron D'Souza, S. Vijayakumar, S. Schaal
20012 citations
Semantic Scholar
Predicting EMG Activity from Neural Firing in M1with Bayesian Backfitting
Jo-Anne Ting, Aaron D'Souza, S. Schaal
20040 citations
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Online Statistical Robot Learning
S. Schaal, S. Vijayakumar, Aaron D'Souza
20010 citations
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