Robert Peharz

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Franz PernkopfGraz University of TechnologyDirección de correo verificada de tugraz.at
Antonio VergariReader (Associate Professor), University of Edinburgh, UKDirección de correo verificada de ed.ac.uk
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISDirección de correo verificada de cs.tu-darmstadt.de
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleDirección de correo verificada de eng.cam.ac.uk
Martin TrappMachine learning researcher, Aalto UniversityDirección de correo verificada de aalto.fi
Alejandro MolinaAmazonDirección de correo verificada de amazon.com
Karl StelznerTU DarmstadtDirección de correo verificada de cs.tu-darmstadt.de
Sebastian TschiatschekUniversity of ViennaDirección de correo verificada de univie.ac.at
Peter B MarschikGeorg-August University Göttingen, Germany & Karolinska Institutet Stockholm, Sweden & MedicalDirección de correo verificada de medunigraz.at
Pedro DomingosProfessor of Computer Science and Engineering, University of WashingtonDirección de correo verificada de cs.washington.edu
Nicola Di MauroAssociate Professor of Computer Science, University of BariDirección de correo verificada de uniba.it
Xiaoting ShaoTU DarmstadtDirección de correo verificada de cs.tu-darmstadt.de
Florian B. PokornyMedical University of Graz, Austria & Technical University of Munich, GermanyDirección de correo verificada de medunigraz.at
Robert GensDirección de correo verificada de cs.washington.edu
Matthias ZoehrerCTO Flapjack GmbHDirección de correo verificada de flapjack-sdk.com
Alvaro H.C. CorreiaQualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeDirección de correo verificada de cam.ac.uk
Gennaro GalaEindhoven University of TechnologyDirección de correo verificada de tue.nl
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeDirección de correo verificada de cam.ac.uk
Thomas LiebigTU DortmundDirección de correo verificada de tu-dortmund.de

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Robert Peharz

Assistant Professor of AI, TU Graz

Dirección de correo verificada de tugraz.at - Página principal

probabilistic machine learning probabilistic circuits AI for science


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Sparse nonnegative matrix factorization using ℓ0-constraints R Peharz, M Stark, F Pernkopf Machine Learning for Signal Processing (MLSP), 2010 IEEE International …, 2010	217*	2010
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	186	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	142	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	135	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	130	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	129	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	99	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	86	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	78	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	76	2021
Learning selective sum-product networks R Peharz, R Gens, P Domingos 31st International Conference on Machine Learning (ICML2014), 2014	74	2014
Foundations of Sum-Product Networks for Probabilistic Modeling R Peharz Graz University of Technology, SPSC, 2015	69	2015
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	64	2019
Faster attend-infer-repeat with tractable probabilistic models K Stelzner, R Peharz, K Kersting International Conference on Machine Learning, 5966-5975, 2019	63	2019
Resource-efficient neural networks for embedded systems W Roth, G Schindler, B Klein, R Peharz, S Tschiatschek, H Fröning, ... arXiv preprint arXiv:2001.03048, 2020	60*	2020
Bayesian learning of sum-product networks M Trapp, R Peharz, H Ge, F Pernkopf, Z Ghahramani Advances in neural information processing systems 32, 2019	53	2019
Joints in random forests A Correia, R Peharz, CP de Campos Advances in neural information processing systems 33, 11404-11415, 2020	49	2020
Introduction to probabilistic graphical models F Pernkopf, R Peharz, S Tschiatschek Academic Press Library in Signal Processing 1, 989-1064, 2014	48	2014
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	47	2020

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