Signal Processing and Speech Communication Laboratory
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Wolfgang Roth

Student Projects
PhD Theses
  • Journal article Rock J., Roth W., Toth M., Meissner P. & Pernkopf F. (2021) Resource-efficient Deep Neural Networks for Automotive Radar Interference Mitigation. in IEEE Journal on Selected Topics in Signal Processing, 15(4), p. 927-940. [more info] [doi]
  • Conference paper Roth W., Schindler G., Fröning H. & Pernkopf F. (2021) On Resource-Efficient Bayesian Network Classifiers and Deep Neural Networks. in International Conference on Pattern Recognition. [more info]
  • Conference paper Peter D., Roth W. & Pernkopf F. (2021) Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and Quantization. in 25th International Conference on Pattern Recognition. [more info]
  • Preprint Pfeifenberger L., Zöhrer M., Roth W., Schindler G., Fröning H. & Pernkopf F. (2020) Resource-Efficient Speech Mask Estimation for Multi-Channel Speech Enhancement.. [more info]
  • Conference paper Schindler G., Roth W., Pernkopf F. & Fröning H. (2020) Parameterized Structured Pruning for Deep Neural Networks. in 6th International Conference on Machine Learning, Optimization, and Data Science (pp. 16-27). [more info] [doi]
  • Conference paper Huber M., Schindler G., Roth W., Fröning H., Schörkhuber C. & Pernkopf F. (2020) Towards Real-Time Single-Channel Singing-Voice Separation with Pruned Multi-Scaled DenseNets. in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 806-810). [more info] [doi]
  • Conference paper Rock J., Roth W., Meissner P. & Pernkopf F. (2020) Quantized Deep Neural Networks for Radar Interference Mitigation. in 2020 European Conference on Machine Learning - ITEM Workshop. [more info]
  • Conference paper Roth W. & Pernkopf F. (2020) Differentiable TAN Structure Learning for Bayesian Network Classifiers. in 10th International Conference on Probabilistic Graphical Models. [more info]
  • Journal article Roth W. & Pernkopf F. (2020) Bayesian Neural Networks with Weight Sharing Using Dirichlet Processes. in IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(1), p. 246-252. [more info] [doi]
  • Technical report Roth W., Schindler G., Zöhrer M., Pfeifenberger L., Peharz R., Tschiatschek S., Fröning H., Pernkopf F. & Ghahramani Z. (2019) Resource-Efficient Neural Networks for Embedded Systems.. [more info]
  • Conference paper Roth W., Schindler G., Fröning H. & Pernkopf F. (2019) Training Discrete-Valued Neural Networks with Sign Activations Using Weight Distributions.. [more info]
  • Conference paper Aichernig B., Bloem R., Ebrahimi M., Horn M., Pernkopf F., Roth W., Rupp A., Tappler M. & Tranninger M. (2019) Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning. in 31st IFIP International Conference on Testing Software and Systems (pp. 3-21). [more info] [doi]
  • Journal article Roth W., Peharz R., Tschiatschek S. & Pernkopf F. (2018) Hybrid generative-discriminative training of Gaussian mixture models. in Pattern Recognition Letters , 112, p. 131-137. [more info] [doi]
  • Conference paper Pokorny F., Peharz R., Roth W., Zöhrer M., Pernkopf F., Marschik P. & Schuller B. (2016) Manual Versus Automated: The Challenging Routine of Infant Vocalisation Segmentation in Home Videos to Study Neuro(mal)development. in 17th Annual Conference of the International Speech Communication Association (pp. 2997 - 3001). [more info] [doi]
  • Conference paper Roth W. & Pernkopf F. (2016) Variational Inference in Neural Networks using an Approximate Closed-Form Objective.. [more info]