Robert Peharz

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Robert Peharz

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

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  • 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)
  • 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., 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)

  • 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

    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

    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

    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
  • 2014

    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)
  • 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)