| Discovering the unknown: detection of emerging pathogens using a label‐free light‐scattering system B Rajwa, MM Dundar, F Akova, A Bettasso, V Patsekin, E Dan Hirleman, ... Cytometry Part A 77 (12), 1103-1112, 2010 | 53 | 2010 |
| A non-parametric Bayesian model for joint cell clustering and cluster matching: identification of anomalous sample phenotypes with random effects M Dundar, F Akova, HZ Yerebakan, B Rajwa BMC bioinformatics 15 (1), 1-15, 2014 | 41 | 2014 |
| Bayesian nonexhaustive learning for online discovery and modeling of emerging classes M Dundar, F Akova, A Qi, B Rajwa arXiv preprint arXiv:1206.4600, 2012 | 29 | 2012 |
| A machine‐learning approach to detecting unknown bacterial serovars F Akova, M Dundar, VJ Davisson, ED Hirleman, AK Bhunia, JP Robinson, ... Statistical Analysis and Data Mining: The ASA Data Science Journal 3 (5 …, 2010 | 25 | 2010 |
| Self-adjusting models for semi-supervised learning in partially observed settings F Akova, M Dundar, Y Qi, B Rajwa 2012 IEEE 12th International Conference on Data Mining, 21-30, 2012 | 13 | 2012 |
| Region competition via local watershed operators H Tek, F Akova, A Ayvaci 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 11 | 2005 |
| Region competition via local watershed operators H Tek, F Akova, A Ayvaci US Patent 7,394,933, 2008 | 8 | 2008 |
| Generalizations with probability distributions for data anonymization ME Nergiz, S Cetintas, F Akova | 6 | 2008 |
| Digital microbiology: detection and classification of unknown bacterial pathogens using a label-free laser light scatter-sensing system B Rajwa, MM Dundar, F Akova, V Patsekin, E Bae, Y Tang, JE Dietz, ... Sensing Technologies for Global Health, Military Medicine, Disaster Response …, 2011 | 1 | 2011 |
| Non-exhaustive learning for bacteria detection F Akova, D Hirleman, AK Bhunia, B Rajwa, MM Dundar 2009 International Conference on Network-Based Information Systems, 206-211, 2009 | 1 | 2009 |
| A nonparametric Bayesian perspective for machine learning in partially-observed settings F Akova Purdue University, 2013 | | 2013 |
| A Nonparametric Bayesian Perspective for Machine Learning in Partially-Observed Settings F Akova Purdue University, 2013 | | 2013 |
Bartek RajwaPurdue UniversityVerified email at purdue.edu
