Signal Processing and Speech Communication Laboratory
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Robert Peharz

Profile Picture Robert Peharz
Research Programs
PhD Theses
Publications
  • Conference paper Toth C., Knoll C., Pernkopf F. & Peharz R. (2025) Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders. in 28th International Conference on Artificial Intelligence and Statistics, AISTATS 2025. [more info]
  • Conference paper Toth C., Knoll C., Pernkopf F. & Peharz R. (2024) Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders. in 2nd SPIGM - ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling. [more info]
  • Journal article Roth W., Schindler G., Klein B., Peharz R., Tschiatschek S., Fröning H., Pernkopf F. & Ghaharamani Z. (2024) Resource-Efficient Neural Networks for Embedded Systems. in Journal of Machine Learning Research, 25. [more info]
  • Conference paper Toth C., Lorch L., Knoll C., Krause A., Pernkopf F., Peharz R. & Kügelgen J. (2023) Active Bayesian Causal Inference. in 36th Conference on Neural Information Processing Systems. [more info]
  • Conference paper Trapp M., Peharz R., Pernkopf F. & Rassmusen C. (2020) Deep Structured Mixtures of Gaussian Processes. in 23rd International Conference on Artificial Intelligence and Statistics (pp. 2251-2261). [more info]
  • Conference paper Peharz R., Lang S., Vergari A., Stelzner K., Molina A., Trapp M., Broeck G., Kersting K. & Ghahramani Z. (2020) Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits.. in 37th International Conference on Machine Learning (pp. 7563-7574). [more info]
  • 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 Trapp M., Peharz R., Ge H., Pernkopf F. & Ghaharamani Z. (2019) Bayesian Learning of Sum-Product Networks.. [more info]
  • Conference paper Peharz R., Vergari A., Stelzner K., Molina A., Shao X., Trapp M., Kersting K. & Ghahramani Z. (2019) Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning.. [more info]
  • Conference paper Trapp M., Peharz R., Rassmusen C. & Pernkopf F. (2018) Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks.. [more info]
  • 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]
  • Journal article Marschik P., Pokorny F., Peharz R., Zhang D., O'Muircheartaigh J., Roeyers H., Bölte S., Spittle A., Urlesberger B., Schuller B., Poustka L., Ozonoff S., Pernkopf F., Pock T., Tammimies K., Enzinger C., Krieber M., Tomantschger I., Bartl-Pokorny K., Sigafoos J., Roche L., Esposito G., Gugatschka M., Nielsen-Saines K., Einspieler C. & Kaufmann W. (2017) A Novel Way to Measure and Predict Development. in Current Neurology and Neuroscience Reports, 17(5), p. 43. [more info] [doi]
  • Conference paper Trapp M., Madl T., Peharz R., Pernkopf F. & Trappl R. (2017) Safe Semi-Supervised Learning of Sum-Product Networks.. [more info]
  • Journal article Peharz R., Gens R., Pernkopf F. & Domingos P. (2017) On the Latent Variable Interpretation in Sum-Product Networks. in IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(10), p. 2030-2044. [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 Schuller B., Peharz R., Pernkopf F., Bartl-Pokorny K., Einspieler C., Marschik P. & Pokorny F. (2016) Retrospektive Analyse frühkindlicher Lautäußerungen in "Home- Videos": Ein signalanalytischer Ansatz zur Früherkennung von Entwicklungsstörungen.. [more info]
  • Conference paper Trapp M., Peharz R., Skowron M., Madl T., Pernkopf F. & Trappl R. (2016) Structure Inference in Sum-Product Networks using Infinite Sum-Product Trees.. [more info]
  • Conference paper Pokorny F., Schuller B., Peharz R., Pernkopf F., Bartl-Pokorny K., Einspieler C. & Marschik P. (2016) Contributing to the early identification of neurodevelopmental disorders: The retrospective analysis of pre-linguistic vocalisations in home video material.. [more info]
  • Conference paper Zöhrer M., Pernkopf F. & Peharz R. (2015) On Representation Learning for Artificial Bandwidth Extension. (pp. 791-795). [more info]
  • Conference paper Peharz R., Tschiatschek S., Pernkopf F. & Domingos P. (2015) On theoretical properties of sum-product networks. (pp. X-x). [more info]
  • Journal article Zöhrer M., Pernkopf F. & Peharz R. (2015) Representation Learning for Single-Channel Source Separation and Bandwidth Extension. in IEEE Transactions on Audio Speech and Language Processing , 23(12), p. 2398-2409. [more info] [doi]
  • Conference paper Peharz R., Gens R. & Domingos P. (2014) Learning Selective Sum-Product Networks. in 31st International Conference on Machine Learning. [more info]
  • Conference paper Peharz R., Kapeller G., Mowlaee Beikzadehmahaleh P. & Pernkopf F. (2014) Modeling Speech with Sum- Product Networks: Application to Bandwidth Extension. in 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (pp. 3699-3703). [more info]
  • Chapter Pernkopf F., Peharz R. & Tschiatschek S. (2014) Introduction to Probabilistic Graphical Models. . [more info]
  • Conference paper Peharz R., Geiger B. & Pernkopf F. (2013) Greedy Part-wise Learning of Sum-Product Networks. (pp. 612-627). [more info]
  • Conference paper Peharz R., Tschiatschek S. & Pernkopf F. (2013) The Most Generative Maximum Margin Bayesian Networks. (pp. 235-243). [more info]
  • Conference paper Peharz R. & Pernkopf F. (2012) Exact Maximum Margin Structure Learning of Bayesian Networks. (pp. X-X). [more info]
  • Conference paper Peharz R. & Pernkopf F. (2012) On Linear and MIXMAX Interaction Models for Single Channel Source Separation. (pp. 249-252). [more info]
  • Journal article Peharz R. & Pernkopf F. (2012) Sparse nonnegative matrix factorization with ℓ0-constraints. in Neurocomputing, 80, p. 38-46. [more info] [doi]
  • Conference paper Peharz R., Wohlmayr M. & Pernkopf F. (2011) Gain-robust Multi-pitch Tracking Using Sparse Nonnegative Matrix Factorization. (pp. 5416-5419). [more info] [doi]
  • Conference paper Wohlmayr M., Peharz R. & Pernkopf F. (2011) Efficient Implementation of Probabilistic Multi-Pitch Tracking. in 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing (pp. 5412-5415). [more info]
  • Conference paper Peharz R., Stark M. & Pernkopf F. (2010) A Factorial Sparse Coder Model for Single Channel Source Separation. in Interspeech - International Conference on Spoken Language Processing (pp. 386-389). [more info]
  • Conference paper Peharz R., Stark M. & Pernkopf F. (2010) Sparse Nonnegative Matrix Factorization using ℓ0-Constraints. in IEEE International Workshop on Machine Learning for Signal Processing (pp. 83-88). [more info]