back to JQ home

Publications

J.A. Quinn and C.K.I. Williams. Physiological Monitoring with Factorial Switching Linear Dynamical Systems, chapter to appear in Probabilistic Methods for Time-Series Analysis, eds. D. Barber, T. Cemgil, S. Chiappa, Cambridge University Press, 2010.

J.R. Aduwo, E. Mwebaze and J.A. Quinn. Automated Vision-Based Diagnosis of Cassava Mosaic Disease, Workshop on Data Mining in Agriculture (DMA 2010), Berlin, 2010.
pdf

E. Mwebaze and J.A. Quinn. Finding Predictive Relationships Between Notifiable Diseases with Markov Blanket Discovery, Int Conf Computing and ICT Research, Kampala, (local conference) 2010.
[pdf soon]

J.A. Quinn and R. Nakibuule. Traffic Flow Monitoring in Crowded Cities, AAAI Spring Symposium on Artificial Intelligence for Development, Stanford, 2010.
pdf

E. Mwebaze, W. Okori and J.A. Quinn. Causal Structure Learning for Famine Prediction, AAAI Spring Symposium on Artificial Intelligence for Development, Stanford, 2010.
pdf

J.A. Quinn, C.K.I. Williams and N. McIntosh. Factorial Switching Linear Dynamical Systems applied to Physiological Monitoring, IEEE Transactions on Pattern Analysis and Machine Intelligence 31(9):1537-51, 2009.
pdf preprint

M. Mubangizi, E. Mwebaze and J.A. Quinn. Computational Prediction of Cholera Outbreaks, Int Conf Computing and ICT Research, Kampala, (local conference) 2009.
pdf

N. Eagle, J.A. Quinn and A. Clauset. Methodologies for Continuous Cellular Tower Data Analysis, Seventh International Conference on Pervasive Computing, 2009.
pdf

N. Eagle, A. Clauset. and J.A. Quinn. Location Segmentation, Inference and Prediction for Anticipatory Computing, AAAI Spring Symposium on Technosocial Predictive Analytics, Stanford, 2009.
pdf

E. Mwebaze and J.A. Quinn. Fast Committee-Based Structure Learning, NIPS Workshop on Causality, 2008. Honourable mention at the workshop challenge for "significant advance on the REGED dataset".
pdf preprint

J.A. Quinn and C.K.I. Williams. Signal Masking in Gaussian Channels, IEEE International Conference on Acoustics, Speech and Signal Processing, 2008.
pdf

C. Fox and J. Quinn. How to be Lost: Principled Pruning and Priming with Particles for Score Following, Proc International Computer Music Conference (ICMC) 2007.
pdf

J.A. Quinn. Bayesian Condition Monitoring in Neonatal Intensive Care. PhD thesis, University of Edinburgh, 2007.
pdf

J.A. Quinn and C.K.I. Williams. Known Unknowns: Novelty Detection in Condition Monitoring, Invited paper in Proc 3rd Iberian Conference on Pattern Recognition and Image Analysis, 2007, Springer LNCS.
pdf

C.K.I. Williams, J.A. Quinn, N. McIntosh. Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care, Advances in Neural Information Processing Systems 18, 2006, MIT Press.
pdf

A.S. Law, Y. Freer, J.R.W. Hunter, R.H. Logie, N. McIntosh, J.A. Quinn. A Comparison of Graphical and Textual Presentations of Time Series Data to Support Medical Decision Making in the Neonatal Intensive Care Unit, Journal of Clinical Monitoring and Computing 19;183-194, 2005.
pdf