Franz Pernkopf

2018
2017
Messner, E., Hagmüller M., Swatek P., Smolle-Jüttner F. - M., & Pernkopf F. (2017).  Respiratory Airflow Estimation from Lung Sounds Based on Regression. in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'17). 1123–1127. Abstract
Messner, E., Hagmüller M., Swatek P., Smolle-Jüttner F. - M., & Pernkopf F. (2017).  Impact of Airflow Rate on Amplitude and Regional Distribution of Normal Lung Sounds. in Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSIGNALS'17). 49 - 53.
Trapp, M., Madl T., Peharz R., Pernkopf F., & Trappl R. (2017).  Safe Semi-Supervised Learning of Sum-Product Networks. Conference on Uncertainty in Artificial Intelligence (UAI). Abstract  Download: cameraready_version.pdf (1.98 MB)
2016
Knoll, C., Pernkopf F., Mehta D., & Chen T. (2016).  Fixed Points Solutions of Belief Propagation. Neural Information Processing Systems (NIPS) workshop.  Download: KnollEtAl2016.pdf (313.3 KB)
Peharz, R., Gens R., Pernkopf F., & Domingos P. (2016).  On the Latent Variable Interpretation in Sum-Product Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence.  Download: 1601.06180.pdf (649.55 KB)
Aichernig, B., Bloem R., Pernkopf F., Röck F., Schrank T., & Tappler M. (2016).  Poster: Learning Models of a Network Protocol using Neural Network Language Models. IEEE Symposium on Security and Privacy, {SP} 2016, San Jose, CA, USA, May 22-26, 2016.
Messner, E., Hagmüller M., Swatek P., & Pernkopf F. (2016).  A Robust Multichannel Lung Sound Recording Device. in Proceedings of the 9th Annual International Conference on Biomedical Electronics and Devices (BIODEVICES'16).
Trapp, M., Peharz R., Skowron M., Madl T., Pernkopf F., & Trappl R. (2016).  Structure Inference in Sum-Product Networks using Infinite Sum-Product Trees. Practical Bayesian Nonparametrics Workshop at the Annual Conference on Neural Information Processing Systems (NIPS).  Download: BNPNIPS_2016_paper_9.pdf (1.16 MB)