Publications

2016

J.A. Quinn, R. Nakasi, P.K. Mugagga, P. Byanyima, W. Lubega, A. Andama.
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics. Proceedings of the International Conference on Machine Learning for Health Care, Journal of Machine Learning Research W&C track, Volume 56, 2016. [pdf]

2015

R. Andrade-Pacheco, M. Mubangizi, J.A. Quinn, N. Lawrence. Monitoring Short Term Changes of Malaria Incidence in Uganda with Gaussian Processes. Proceedings of the ECML/PKDD Workshop on Advanced Analytics and Learning on Temporal Data, 2015. [pdf]

2014

J.A. Quinn, A. Andama, I. Munabi, F.N. Kiwanuka. Automated Blood Smear Analysis for Mobile Malaria Diagnosis. In Mobile Point-of-Care Monitors and Diagnostic Device Design, eds. W. Karlen and K. Iniewski, CRC Press, 2014. [pdf] [code]

J.A. Quinn, V. Frias-Martinez, L. Subramanian. Computational Sustainability and Artificial Intelligence in the Developing World. Artificial Intelligence Magazine, Fall 2014. [pdf]

I.Ndibatya, MJ Booysen. Modelling of inter-stop minibus taxi movements: Using machine learning and network theory. Proceedings of the 1st International Conference on the Use of Mobile ICT in Africa. 9-10 December 2014, Stellenbosch, South Africa. [pdf]

Ndibatya, I., M. J. Booysen, and J. Quinn. An adaptive transportation prediction model for the informal public transport sector in Africa. Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on. IEEE, 2014. [pdf]

R. Nakibuule, J.A. Quinn. Performance Evaluation of a Low Cost Vision-Based Traffic Flow Monitoring System. Proceedings of the 1st International Conference on the Use of Mobile ICT in Africa. 9-10 December 2014, Stellenbosch, South Africa. [pdf]

M. Mubangizi, R. Andrade-Pacheco, M. Smith, J.A. Quinn and N.D. Lawrence. Malaria surveillance with multiple data sources using Gaussian process models. Proceedings of the 1st International Conference on the Use of Mobile ICT in Africa. 9-10 December 2014, Stellenbosch, South Africa. [pdf]

J. Tuhaise, J.A. Quinn, E. Mwebaze. Pixel Classification Methods for Automatic Symptom Measurement of Cassava Brown Streak Disease. Proceedings of the 1st International Conference on the Use of Mobile ICT in Africa. 9-10 December 2014, Stellenbosch, South Africa. [pdf]

G. Owomugisha, J.A. Quinn, E. Mwebaze, J. Lwasa. Automated Vision-Based Diagnosis of Banana Bacterial Wilt Disease and Black Sigatoka Disease. Proceedings of the 1st International Conference on the Use of Mobile ICT in Africa. 9-10 December 2014, Stellenbosch, South Africa. [pdf]

J.A. Quinn, M. Sugiyama. A Least-Squares Approach to Anomaly Detection in Static and Sequential Data. Pattern Recognition Letters 40:36-40, 2014. [pdf]

S. Liu, J.A. Quinn, M.U. Gutmann, T. Suzuki, M. Sugiyama. Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation. Neural Computation 26.6 (2014): 1169-1197. [pdf] [code]

2013

R. Ssekibuule, J.A. Quinn, K Leyton-Brown. A Mobile Market for Agricultural Trade in Uganda. The Fourth Annual Symposium on Computing for Development (ACM DEV), 2013. [pdf]

J.A. Quinn. Computational Techniques for Crop Disease Monitoring in the Developing World. Invited paper in The Twelfth International Symposium on Intelligent Data Analysis, Advances in Intelligent Data Analysis (12) 13-18, 2013, Springer LNCS. [pdf]

R Nakibuule, J Ssenyange, J.A. Quinn. Low Cost Video-Based Traffic Congestion Monitoring Using Phones As Sensors. Poster in The Third Annual Symposium on Computing for Development (ACM DEV), 2013. [pdf]

2012

M. Mubangizi, C. Ikae, A. Spiliopoulou, J.A. Quinn. Coupling Spatiotemporal Disease Modeling with Diagnosis. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), 2012. [pdf]

2011

W. Okori and J. Obua. Supervised Learning Algorithms for Famine Prediction. Journal of Applied Artificial Intelligence 25(9):822-835, 2011. [pdf]

J.A. Quinn, K. Leyton-Brown, E. Mwebaze. Modeling and Monitoring Crop Disease in Developing Countries. Conference of the Association for the Advancement of Artificial Intelligence (AAAI), 2011. [pdf]

E. Mwebaze, P. Schneider, F.-M. Schleif, J.R. Aduwo, J.A. Quinn, S. Haase, T. Villmann, M. Biehl. Divergence based classification in Learning Vector Quantization , Neurocomputing 74(9):1429-1435, 2011. [pdf]

E. Mwebaze, M. Biehl, J.A. Quinn. Causal Relevance Learning for Robust Classification under Interventions, To appear in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2011.[pdf]

J.A. Quinn, J. Mooij, T. Heskes, M. Biehl. Learning of Causal Relations, Invited paper in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2011. [pdf]

2010

J.A. Quinn, W. Okori and A. Gidudu. Increased-Specificity Famine Prediction using Satellite Observation Data, To appear in The First Annual Symposium on Computing for Development (ACM DEV), London, 2010. [pdf]

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

W. Okori, J. Obua and V. Baryamureeba. Logit Analysis of Socio-Economic Factors Influencing Famine Disaster in Uganda. Journal of Disaster Research, 5(3), 2010. [pdf]

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, P. Schneider, F.-M. Schleif, S. Haase, T. Villmann, M. Biehl. Divergence based Learning Vector Quantization, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2010. [pdf]

E. Mwebaze and J.A. Quinn. Fast Committee-Based Structure Learning. NIPS 2008 Workshop on Causality, Journal of Machine Learning Research Workshop and Conference Proceedings 6:203–214. [pdf]

2009

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]