Barber, D., Cemgil, A., Chiappa, S.
Bayesian Time Series Models
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)
Chiappa, S., Peters, J.
Movement extraction by detecting dynamics switches and repetitions
In Advances in Neural Information Processing Systems 23, pages: 388-396, (Editors: Lafferty, J. , C. K.I. Williams, J. Shawe-Taylor, R. S. Zemel, A. Culotta), Curran, Red Hook, NY, USA, Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS), 2010 (inproceedings)
Chiappa, S., Kober, J., Peters, J.
Using Bayesian Dynamical Systems for Motion Template Libraries
In Advances in neural information processing systems 21, pages: 297-304, (Editors: Koller, D. , D. Schuurmans, Y. Bengio, L. Bottou), Curran, Red Hook, NY, USA, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS), June 2009 (inproceedings)
Chiappa, S., Saigo, H., Tsuda, K.
A Bayesian Approach to Graph Regression with Relevant Subgraph Selection
In SIAM International Conference on Data Mining, pages: 295-304, (Editors: Park, H. , S. Parthasarathy, H. Liu), Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, SDM, May 2009 (inproceedings)
Chiappa, S.
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
In ICMLA 2008, pages: 3-9, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. Kurgan, T. Hu, K. Hafeez), IEEE Computer Society, Los Alamitos, CA, USA, 7th International Conference on Machine Learning and Applications, December 2008 (inproceedings)
Chiappa, S.
Variational Bayesian Model Selection in Linear Gaussian State-Space based Models
International Workshop on Flexible Modelling: Smoothing and Robustness (FMSR 2008), 2008, pages: 1, November 2008 (poster)
Chiappa, S.
Unsupervised Bayesian Time-series Segmentation based on Linear Gaussian State-space Models
(171), Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, June 2008 (techreport)
Chiappa, S., Barber, D.
Output Grouping using Dirichlet Mixtures of Linear Gaussian State-Space Models
In ISPA 2007, pages: 446-451, IEEE Computer Society, Los Alamitos, CA, USA, 5th International Symposium on Image and Signal Processing and Analysis, September 2007 (inproceedings)
Chiappa, S., Barber, D.
Dirichlet Mixtures of Bayesian Linear Gaussian State-Space Models: a Variational Approach
(161), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, March 2007 (techreport)