• Bron: Scopus
20102021

Onderzoeksresultaten per jaar

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Persoonlijk profiel

Academic background

Robert Peharz received his Master degree in Computer Engineering from Graz University of Technology (TU Graz), Austria (2010). From 2010-2015, he pursued his PhD studies at TU Graz, working on probabilistic graphcial models and sum-product networks, with applications to signal processing. From 2015-2017, he was postdoc at the Medical University of Graz, working on interdisciplinary approaches for early recognition of neural maldevelopment via behavioral neuroscience. He was postdoc in the Machine Learning Group (MLG) at the University of Cambridge from 2017-2018. He was Marie-Curie Individual Fellow at MLG Cambridge from 2018-2019. Robert joined Eindhoven University of Technology (TU/e) in November 2019 as an Assistant Professor in the Artificial Intelligence cluster.

Quote

Uncertainty Matters

Research profile

Robert Peharz is an Assistant Professor in the Artificial Intelligence cluster at Eindhoven University of Technology. Robert's work leverages probability as a principled language to represent and process uncertain knowledge. His main research activity is dedicated to develop powerful and expressive machine learning algorithms which are based on probabilistic principles. His particular research targets are probabilistic graphical models, tractable probabilistic models such as probabilistic circuits, and probabilistic deep learning. In his work, Robert aims to unite principled probabilistic modeling with the power of the entire machine learning toolbox.

Expertise gerelateerd aan duurzame ontwikkelingsdoelstellingen van de VN

In 2015 stemden de VN-lidstaten in met 17 wereldwijde duurzame ontwikkelingsdoelstellingen (Sustainable Development Goals, SDG's) om armoede te beëindigen, de planeet te beschermen en voor iedereen welvaart te garanderen. Het werk van deze persoon draagt bij aan de volgende duurzame ontwikkelingsdoelstelling(en):

  • SDG 7 – Betaalbare en schone energie

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Verdiep u in de onderzoeksgebieden waarop Robert Peharz actief is. Deze onderwerplabels komen uit het werk van deze persoon. Samen vormen ze een unieke vingerafdruk.
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  • 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. (redactie). Springer, blz. 68-84 17 blz. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12461 LNAI).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    1 Citaat (Scopus)
  • 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. (redactie). blz. 2251-2261 10 blz. (Proceedings of Machine Learning Research (PMLR); vol. 108).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    Open Access
  • 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. (redactie). Curran Associates, blz. 11404-11415 12 blz. (Advances in Neural Information Processing Systems; nr. 33).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    Open Access
    3 Citaten (Scopus)
  • Joints in Random Forests

    Correia, A. H. C., Peharz, R. & Campos, C. P. D., 2020, (Geaccepteerd/In druk) In: Proceedings of Machine Learning Research. XX, XX

    Onderzoeksoutput: Bijdrage aan tijdschriftCongresartikelAcademicpeer review

    Open Access
    Bestand
    30 Downloads (Pure)
  • 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.

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    Bestand
    21 Downloads (Pure)