Robert Peharz
Department / Institute
Group
![](https://assets.w3.tue.nl/w/fileadmin/_processed_/d/6/csm_149668ea94b8a8041a391ce07d81781e_3090aabae0.jpg)
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.
Uncertainty Matters
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.
Recent Publications
-
Probabilistic Integral Circuits
(2024) -
Continuous mixtures of tractable probabilistic models
(2023) -
Bayesian Structure Scores for Probabilistic Circuits
(2023) -
PS3
(2021) -
Towards Robust Classification with Deep Generative Forests
(2020)
Ancillary Activities
No ancillary activities