Robert Peharz

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	Toate	Din 2020
Referințe bibliografice	2503	1796
h-index	27	24
i10-index	39	34

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Franz PernkopfGraz University of TechnologyAdresă de e-mail confirmată pe tugraz.at
Antonio VergariReader (Associate Professor), University of Edinburgh, UKAdresă de e-mail confirmată pe ed.ac.uk
Kristian KerstingProfessor of AI & ML, Technical University of Darmstadt, Co-Director hessian.ai, DFKI, CAIRNE, ELLISAdresă de e-mail confirmată pe cs.tu-darmstadt.de
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresă de e-mail confirmată pe eng.cam.ac.uk
Martin TrappMachine learning researcher, Aalto UniversityAdresă de e-mail confirmată pe aalto.fi
Alejandro MolinaAmazonAdresă de e-mail confirmată pe amazon.com
Karl StelznerTU DarmstadtAdresă de e-mail confirmată pe cs.tu-darmstadt.de
Sebastian TschiatschekUniversity of ViennaAdresă de e-mail confirmată pe univie.ac.at
Peter B MarschikGeorg-August University Göttingen, Germany & Karolinska Institutet Stockholm, Sweden & MedicalAdresă de e-mail confirmată pe medunigraz.at
Pedro DomingosProfessor of Computer Science and Engineering, University of WashingtonAdresă de e-mail confirmată pe cs.washington.edu
Nicola Di MauroAssociate Professor of Computer Science, University of BariAdresă de e-mail confirmată pe uniba.it
Xiaoting ShaoTU DarmstadtAdresă de e-mail confirmată pe cs.tu-darmstadt.de
Florian B. PokornyMedical University of Graz, Austria & Technical University of Munich, GermanyAdresă de e-mail confirmată pe medunigraz.at
Robert GensAdresă de e-mail confirmată pe cs.washington.edu
Alvaro H.C. CorreiaQualcomm AI ResearchAdresă de e-mail confirmată pe qti.qualcomm.com
Matthias ZoehrerCTO Flapjack GmbHAdresă de e-mail confirmată pe flapjack-sdk.com
Gennaro GalaEindhoven University of TechnologyAdresă de e-mail confirmată pe tue.nl
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeAdresă de e-mail confirmată pe cam.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeAdresă de e-mail confirmată pe cam.ac.uk
Thomas LiebigTU DortmundAdresă de e-mail confirmată pe tu-dortmund.de

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Robert Peharz

Assistant Professor of AI, TU Graz

Adresă de e-mail confirmată pe tugraz.at - Pagina de pornire

probabilistic machine learning probabilistic circuits AI for science


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
Sparse nonnegative matrix factorization with ℓ0-constraints R Peharz, F Pernkopf Neurocomputing 80, 38-46, 2012	222	2012
Fidgety movements–tiny in appearance, but huge in impact C Einspieler, R Peharz, PB Marschik Jornal de pediatria 92 (3 Suppl 1), 64-70, 2016	195	2016
On the latent variable interpretation in sum-product networks R Peharz, R Gens, F Pernkopf, P Domingos IEEE transactions on pattern analysis and machine intelligence 39 (10), 2030 …, 2016	145	2016
On Theoretical Properties of Sum-Product Networks R Peharz, S Tschiatschek, F Pernkopf, P Domingos Proceedings of the Eighteenth International Conference on Artificial …, 2015	142	2015
Random sum-product networks: A simple and effective approach to probabilistic deep learning R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ... Uncertainty in Artificial Intelligence, 334-344, 2020	135	2020
Einsum networks: Fast and scalable learning of tractable probabilistic circuits R Peharz, S Lang, A Vergari, K Stelzner, A Molina, M Trapp, ... International Conference on Machine Learning, 7563-7574, 2020	133	2020
A novel way to measure and predict development: A heuristic approach to facilitate the early detection of neurodevelopmental disorders PB Marschik, FB Pokorny, R Peharz, D Zhang, J O’Muircheartaigh, ... Current neurology and neuroscience reports 17, 1-15, 2017	107	2017
Greedy part-wise learning of sum-product networks R Peharz, BC Geiger, F Pernkopf Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013	91	2013
Modeling speech with sum-product networks: Application to bandwidth extension R Peharz, G Kapeller, P Mowlaee, F Pernkopf 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014	88	2014
Minimal random code learning: Getting bits back from compressed model parameters M Havasi, R Peharz, JM Hernández-Lobato arXiv preprint arXiv:1810.00440, 2018	85	2018
Novel AI driven approach to classify infant motor functions S Reich, D Zhang, T Kulvicius, S Bölte, K Nielsen-Saines, FB Pokorny, ... Scientific Reports 11 (1), 9888, 2021	82	2021
Learning selective sum-product networks R Peharz, R Gens, P Domingos 31st International Conference on Machine Learning (ICML2014), 2014	76	2014
Foundations of Sum-Product Networks for Probabilistic Modeling R Peharz Graz University of Technology, SPSC, 2015	71	2015
Resource-Efficient Neural Networks for Embedded Systems W Roth, G Schindler, B Klein, R Peharz, S Tschiatschek, H Fröning, ... Journal of Machine Learning Research 25 (50), 1-51, 2024	69	2024
Spflow: An easy and extensible library for deep probabilistic learning using sum-product networks A Molina, A Vergari, K Stelzner, R Peharz, P Subramani, N Di Mauro, ... arXiv preprint arXiv:1901.03704, 2019	68	2019
Faster attend-infer-repeat with tractable probabilistic models K Stelzner, R Peharz, K Kersting International Conference on Machine Learning, 5966-5975, 2019	64	2019
Bayesian learning of sum-product networks M Trapp, R Peharz, H Ge, F Pernkopf, Z Ghahramani Advances in neural information processing systems 32, 2019	57	2019
Joints in random forests A Correia, R Peharz, CP de Campos Advances in neural information processing systems 33, 11404-11415, 2020	53	2020
Conditional sum-product networks: Imposing structure on deep probabilistic architectures X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting International Conference on Probabilistic Graphical Models, 401-412, 2020	50	2020
Introduction to probabilistic graphical models F Pernkopf, R Peharz, S Tschiatschek Academic Press Library in signal processing 1, 989-1064, 2014	50	2014

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