Franz Pernkopf

Ratajczak, M., Tschiatschek S., & Pernkopf F. (2014).  Context-Speci c Deep Conditional Random Fields for Structured Prediction. International Conference on Machine Learning (ICML), Workshop on Learning Tractable Probabilistic Models.  Download: ltpm2014_submission_4_accepted.pdf (314.24 KB)
Zöhrer, M., & Pernkopf F. (2014).  General Stochastic Networks for Classifi cation. Neural Information Processing Systems (NIPS).
Tschiatschek, S., Paul K., & Pernkopf F. (2014).  Integer Bayesian Networks. European Conference on Machine Learning (ECML).  Download: main_1.pdf (407.69 KB)
Pernkopf, F., Peharz R., & Tschiatschek S. (2014).  Introduction to Probabilistic Graphical Models. Academic Press Library in Signal Processing, Vol. 1, Ch. 18. 989-1064. Download: PGM.pdf (825.41 KB)
Mowlaee, P., Morales-Cordovilla J. A., Pernkopf F., Pessentheiner H., Hagmüller M., & Kubin G. (2013).  The 2nd ‘CHIME’ Speech Separation and Recognition Challenge: Approaches on Single-channel Speech Separation and Model-driven Speech Enhancement. in Proceeding of the 2nd CHiME Speech Separation and Recognition Challenge, IEEE Int. Conf. Acoustics, Speech, Signal Processing, May. 2013, . 59-64.
Tschiatschek, S., Chacon C. C., & Pernkopf F. (2013).  Bound for Bayesian Network Classifiers with Reduced Precision Parameters. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 3357- 3361. Download: main.pdf (97.51 KB)
Leitner, C., & Pernkopf F. (2013).  Generalization of Pre-Image Iterations for Speech Enhancement. International Conference on Acoustics, Speech, and Signal Processing (ICASSP). 7010-7014.