Robert Peharz

1.3k citations
29 papers · 483 · h-index 10

Impact in

Papers in

    • Bayesian Modeling and Causal Inference 8
    • Machine Learning and Data Classification 6
    • Gaussian Processes and Bayesian Inference 6
    • Speech Recognition and Synthesis 5
    • Speech and Audio Processing 7
    • Music and Audio Processing 6

Robert Peharz

28 papers receiving 468 citations

Peers

Robert Peharz
Comparison fields: 5 of 89
  • Signal Processing 90
  • Pediatrics, Perinatology and Child Health 137
  • Computational Mathematics 4
  • Computer Vision and Pattern Recognition 109
  • Artificial Intelligence 136
Replace Liangjun Chen with:
Liangjun Chen China
N.B. Karayiannis United States
Vamsi Krishna Ithapu United States
Gerard Sanromà Spain
Lili He United States
Steffen Oeltze Germany
K.L. Oehler United States
Stéphanie Allassonnière France
Zhenming Yuan China
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Citations per field
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Citations per year

Countries citing papers authored by Robert Peharz

Since Specialization
Citations

This map shows the geographic impact of Robert Peharz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Robert Peharz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Peharz more than expected).

Fields of papers citing papers by Robert Peharz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Peharz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robert Peharz. The network helps show where Robert Peharz may publish in the future.

Co-authors

The 25 scholars most cited alongside Robert Peharz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robert Peharz Line = papers co-authored together Robert Peharz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016124
2 2011115
3 202161
4 201428
5
{On Theoretical Properties of Sum-Product Networks}
201525
6
Learning Selective Sum-Product Networks
201417
7 201515
8 201914
9 201610
10 20109
11 20169
12
Faster Attend-Infer-Repeat with Tractable Probabilistic Models.
20198
13 20186
14 20185
15 20115
16
Bayesian Learning of Sum-Product Networks
20194
17
The Most Generative Maximum Margin Bayesian Networks
20133
18 20233
19 20113
20 20123

About Robert Peharz

Robert Peharz is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Pediatrics, Perinatology and Child Health and Computational Mechanics, having authored 29 papers that have together received 483 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (8 papers), Speech and Audio Processing (7 papers), Music and Audio Processing (6 papers), Machine Learning and Data Classification (6 papers), Gaussian Processes and Bayesian Inference (6 papers), Speech Recognition and Synthesis (5 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Infant Development and Preterm Care (3 papers). The work is most often cited by research in Signal Processing (90 citations), Pediatrics, Perinatology and Child Health (137 citations), Computational Mathematics (4 citations), Computer Vision and Pattern Recognition (109 citations) and Artificial Intelligence (136 citations). Robert Peharz has collaborated with scholars based in Austria, United Kingdom and Germany. Frequent co-authors include Franz Pernkopf, Peter B. Marschik, Christa Einspieler, Pedro Domingos, Sebastian Tschiatschek, Pejman Mowlaee, Florian B. Pokorny, Kristian Kersting, Tomas Kulvičius and Sven Bölte. Their work appears in journals such as Pattern Recognition Letters, Jornal de Pediatria, Neurocomputing, International Journal of Approximate Reasoning and IEEE/ACM Transactions on Audio Speech and Language Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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