Robert Peharz

View Scopus Profile

Robert Peharz

 https://orcid.org/0000-0002-8644-9655
  • 745
    Citations - based on content available in repository [source: Scopus]
20102025

Content available in repository

Search results

  • 2025

    What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?

    Loconte, L., Mari, A., Gala, G., Peharz, R., de Campos, C., Quaeghebeur, E., Vessio, G. & Vergari, A., Feb 2025, In: Transactions on Machine Learning Research. 2025, 02, 56 p.

    Research output: Contribution to journal › Article › Academic › peer-review

    Open Access
    File
    7 Downloads (Pure)
  • 2024

    Probabilistic Integral Circuits

    Gala, G., de Campos, C., Peharz, R., Vergari, A. & Quaeghebeur, E., 4 May 2024, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics. Dasgupta, S., Mandt, S. & Li, Y. (eds.). PMLR, p. 2143-2151 9 p. (Proceedings of Machine Learning Research (PMLR); vol. 238).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    4 Citations (Scopus)
    3 Downloads (Pure)

  • What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?

    Loconte, L., Mari, A., Gala, G., Peharz, R., de Campos, C., Quaeghebeur, E., Vessio, G. & Vergari, A., 2024.

    Research output: Working paper › Preprint › Academic › peer-review

  • 2023

    Bayesian Structure Scores for Probabilistic Circuits

    Yang, Y., Gala, G. & Peharz, R., 2023, Proceedings of The 26th International Conference on Artificial Intelligence and Statistics. Ruiz, F., Dy, J. & van de Meent, J.-W. (eds.). PMLR, p. 563-575 13 p. (Proceedings of Machine Learning Research; vol. 206).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    3 Citations (Scopus)

  • Continuous mixtures of tractable probabilistic models

    Correia, A. H. C., Gala, G., Quaeghebeur, E., de Campos, C. P. & Peharz, R., 26 Jun 2023, Proceedings of the 37th AAAI Conference on Artificial Intelligence. Williams, B., Chen, Y. & Neville, J. (eds.). AAAI Press, p. 7244-7252 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 37, no. 6).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    13 Citations (Scopus)
    54 Downloads (Pure)
  • 2021

    PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data

    Fajri, R., Khoshrou, S., Peharz, R. & Pechenizkiy, M., 2021, Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track - European Conference, ECML PKDD 2020, Proceedings. Dong, Y., Mladenic, D. & Saunders, C. (eds.). Springer, p. 68-84 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12461 LNAI).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    1 Citation (Scopus)
  • 2020

    Deep Structured Mixtures of Gaussian Processes

    Trapp, M., Peharz, R., Pernkopf, F. & Rasmussen, C. E., 26 Apr 2020, Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (PMLR). Chiappa, S. & Calandra, R. (eds.). p. 2251-2261 11 p. (Proceedings of Machine Learning Research (PMLR); vol. 108).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    19 Citations (Scopus)

  • Joints in Random Forests

    Correia, A. H. C., Peharz, R. & Campos, C. P. D., 2020. 12 p.

    Research output: Contribution to conference › Paper › Academic

    Open Access
    File
    95 Downloads (Pure)

  • Joints in Random Forests

    Correia, A., Peharz, R. & de Campos, C. P., 2020, Advances in Neural Information Processing Systems. Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F. & Lin, H. (eds.). Curran Associates, p. 11404-11415 12 p. (Advances in Neural Information Processing Systems; vol. 33).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    25 Citations (Scopus)

  • Towards Robust Classification with Deep Generative Forests

    Correia, A. H. C., Peharz, R. & Campos, C. D., 11 Jul 2020, ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    File
    43 Downloads (Pure)
  • 2019

    Automatic Bayesian Density Analysis

    Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K. & Valera, I., 2019, Proceedings of The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19). AAAI Press, p. 5207-5215 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access

  • Bayesian Learning of Sum-Product Networks

    Trapp, M., Peharz, R., Ge, H., Pernkopf, F. & Ghahramani, Z., 26 May 2019, Advances in Neural Information Processing Systems (NeurIPS). Curran Associates, p. 6347-6358 (Advances in Neural Information Processing Systems; vol. 32).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    35 Citations (Scopus)

  • Encoding and decoding representations with sum- And max-product networks

    Vergari, A., Peharz, R., Di Mauro, N. & Esposito, F., 1 Jan 2019.

    Research output: Contribution to conference › Paper › Academic

  • Faster attend-infer-repeat with tractable probabilistic models

    Stelzner, K., Peharz, R. & Kersting, K., 1 Jan 2019, 36th International Conference on Machine Learning, ICML 2019. p. 10455-10466 12 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    14 Citations (Scopus)

  • Hierarchical decompositional mixtures of variational autoencoders

    Tan, P. L. & Peharz, R., 1 Jan 2019, 36th International Conference on Machine Learning, ICML 2019. p. 10701-10711 11 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    3 Citations (Scopus)

  • Minimal random code learning: Getting bits back from compressed model parameters

    Havasi, M., Peharz, R. & Hernández-Lobato, J. M., 1 Jan 2019, International Conference on Learning Representations.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • Random sum-product networks: A simple and effective approach to probabilistic deep learning

    Peharz, R., Vergari, A., Stelzner, K., Molina, A., Shao, X., Trapp, M., Kersting, K. & Ghahramani, Z., 2019, Conference on Uncertainty in Artificial Intelligence (UAI).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    31 Citations (Scopus)
  • 2018

    Hybrid generative-discriminative training of Gaussian mixture models

    Roth, W., Peharz, R., Tschiatschek, S. & Pernkopf, F., 1 Sept 2018, In: Pattern Recognition Letters. 112, p. 131-137 7 p.

    Research output: Contribution to journal › Article › Academic › peer-review

    10 Citations (Scopus)

  • Sum-product autoencoding: Encoding and decoding representations using sum-product networks

    Vergari, A., Molina, A., Peharz, R., Kersting, K., Mauro, N. D. & Esposito, F., 1 Jan 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI Press, p. 4163-4170 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    15 Citations (Scopus)
  • 2017

    A novel way to measure and predict development: A heuristic approach to facilitate the early detection of neurodevelopmental disorders

    Marschik, P. B., Pokorny, F. B., Peharz, R., Zhang, D., O’Muircheartaigh, J., Roeyers, H., Bölte, S., Spittle, A. J., Urlesberger, B., Schuller, B., Poustka, L., Ozonoff, S., Pernkopf, F., Pock, T., Tammimies, K., Enzinger, C., Krieber, M., Tomantschger, I., Bartl-Pokorny, K. D. & Sigafoos, J. & 6 others, Roche, L., Esposito, G., Gugatschka, M., Nielsen-Saines, K., Einspieler, C. & Kaufmann, W. E., 1 May 2017, In: Current Neurology and Neuroscience Reports. 17, 5, 15 p., 43.

    Research output: Contribution to journal › Review article › peer-review

    Open Access
    82 Citations (Scopus)

  • On the latent variable interpretation in sum-product networks

    Peharz, R., Gens, R., Pernkopf, F. & Domingos, P., 1 Oct 2017, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 39, 10, p. 2030-2044 15 p., 7748514.

    Research output: Contribution to journal › Article › Academic › peer-review

    Open Access
    62 Citations (Scopus)

  • Safe semi-supervised learning of sum-product networks

    Trapp, M., Madl, T., Peharz, R., Pernkopf, F. & Trappl, R., 1 Jan 2017, Conference on Uncertainty in Artificial Intelligence (UAI). 10 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

  • 2016

    Fidgety movements – tiny in appearance, but huge in impact

    Einspieler, C., Peharz, R. & Marschik, P., 2016, In: Jornal de Pediatria. 92, 3, p. 64-70

    Research output: Contribution to journal › Article › Academic › peer-review

    Open Access
    113 Citations (Scopus)

  • Manual versus automated: The challenging routine of infant vocalisation segmentation in home videos to study neuro(mal)development

    Pokorny, F. B., Peharz, R., Roth, W., Zöhrer, M., Pernkopf, F., Marschik, P. B. & Schuller, B. W., 1 Jan 2016, Interspeech 2016 8-12 Sep 2016, San Francisco. Morgan, N. (ed.). ISCA, p. 2997-3001 5 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    12 Citations (Scopus)
  • 2015

    On representation learning for artificial bandwidth extension

    Zöhrer, M., Peharz, R. & Pernkopf, F., 1 Jan 2015, Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. ISCA, p. 791-795 5 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    3 Citations (Scopus)

  • On theoretical pProperties of sum-product networks

    Peharz, R., Tschiatschek, S., Pernkopf, F. & Domingos, P., 2015, Proceedings of the Conference on Artificial Intelligence and Statistics (AISTATS). p. 744-752 (Proceedings of Machine Learning Research; vol. 18).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access

  • Representation Learning for Single-Channel Source Separation and Bandwidth Extension

    Zoehrer, M., Peharz, R. & Pernkopf, F., 2015, In: IEEE Transactions on Audio, Speech, and Language Processing. 23, 12, p. 2398 - 2409

    Research output: Contribution to journal › Article › Academic › peer-review

    17 Citations (Scopus)
  • 2014

    Introduction to probabilistic graphical models

    Pernkopf, F., Peharz, R. & Tschiatschek, S., 2014, Academic Press Library in Signal Processing: Volume 1: Signal processing theory and machine learning. Diniz, P. S. R., Suykens, J. A. K., Chellappa, R. & Theodoridis, S. (eds.). Elsevier, Vol. 1. p. 989-1064

    Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

  • Learning selective sum-product networks

    Peharz, R., Gens, R. & Domingos, P., 2014.

    Research output: Contribution to conference › Paper › Academic

    Open Access
    File
    63 Downloads (Pure)

  • Modeling speech with sum-product networks: Application to bandwidth extension

    Peharz, R., Kapeller, G., Mowlaee, P. & Pernkopf, F., 1 Jan 2014, 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014. Institute of Electrical and Electronics Engineers, p. 3699-3703 5 p. 6854292

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    52 Citations (Scopus)
  • 2013

    Greedy part-wise learning of sum-product networks

    Peharz, R., Geiger, B. & Pernkopf, F., 2013, Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013: Proceedings Part 1. Blockeel, H., Kersting, K., Nijssen, S. & Železný, F. (eds.). Springer, p. 612-627 (Lecture Notes in Computer Science; vol. 8188)(Lecture Notes in Artificial Intelligence; vol. 8188).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    47 Citations (Scopus)

  • The most generative maximum margin Bayesian networks

    Peharz, R., Tschiatschek, S. & Pernkopf, F., 1 Jan 2013, International Conference on Machine Learning (ICML). p. 1272-1280 9 p. (Proceedings of Machine Learning Research; vol. 28).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    5 Citations (Scopus)
  • 2012

    Exact maximum margin structure learning of Bayesian networks

    Peharz, R. & Pernkopf, F., 10 Oct 2012, Proceedings of the 29th International Conference on Machine Learning, ICML 2012. p. 1047-1054 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    6 Citations (Scopus)

  • On linear and mixmax interaction models for single channel source separation

    Peharz, R. & Pernkopf, F., 23 Oct 2012, 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings. IEEE Press, p. 249-252 4 p. 6287864

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    5 Citations (Scopus)

  • Sparse nonnegative matrix factorization with ℓ0-constraints

    Peharz, R. & Pernkopf, F., 15 Mar 2012, In: Neurocomputing. 80, p. 38-46 8 p.

    Research output: Contribution to journal › Article › Academic › peer-review

    Open Access
    137 Citations (Scopus)
  • 2011

    Efficient implementation of probabilistic multi-pitch tracking

    Wohlmayr, M., Peharz, R. & Pernkopf, F., 18 Aug 2011, 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. p. 5412-5415 4 p. 5947582

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    3 Citations (Scopus)

  • Gain-robust multi-pitch tracking using sparse nonnegative matrix factorization

    Peharz, R., Wohlmayr, M. & Pernkopf, F., 18 Aug 2011, 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. Institute of Electrical and Electronics Engineers, p. 5416-5419 4 p. 5947583

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    6 Citations (Scopus)
  • 2010

    A factorial sparse coder model for single channel source separation

    Peharz, R., Stark, M., Pernkopf, F. & Stylianou, Y., 1 Dec 2010, Annual Conference of the International Speech Communication Association (INTERSPEECH). ISCA, p. 386-389 4 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    3 Citations (Scopus)

  • Sparse nonnegative matrix factorization using ℓ0-constraints

    Peharz, R., Stark, M. & Pernkopf, F., 24 Nov 2010, Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2010. Institute of Electrical and Electronics Engineers, p. 83-88 6 p. 5589219

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    19 Citations (Scopus)