Michael U. Gutmann

5.4k total citations · 1 hit paper
51 papers, 1.9k citations indexed

About

Michael U. Gutmann is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Signal Processing. According to data from OpenAlex, Michael U. Gutmann has authored 51 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 10 papers in Cognitive Neuroscience and 10 papers in Signal Processing. Recurrent topics in Michael U. Gutmann's work include Blind Source Separation Techniques (9 papers), Gaussian Processes and Bayesian Inference (9 papers) and Neural dynamics and brain function (7 papers). Michael U. Gutmann is often cited by papers focused on Blind Source Separation Techniques (9 papers), Gaussian Processes and Bayesian Inference (9 papers) and Neural dynamics and brain function (7 papers). Michael U. Gutmann collaborates with scholars based in Finland, United Kingdom and Japan. Michael U. Gutmann's co-authors include Aapo Hyvärinen, Jukka Corander, Jun-ichiro Hirayama, Samuel Kaski, Ritabrata Dutta, William P. Hanage, Charles Sutton, Akash Srivastava, Chris Russell and Lazar Valkov and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

Michael U. Gutmann

50 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

2010 626 citations Michael U. Gutmann, Aapo Hyvärinen Edinburgh Research Explorer (University of Edinburgh) profile →

Peers

Countries citing papers authored by Michael U. Gutmann

Since Specialization

Citations

This map shows the geographic impact of Michael U. Gutmann'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 Michael U. Gutmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael U. Gutmann more than expected).

Fields of papers citing papers by Michael U. Gutmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael U. Gutmann. 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 Michael U. Gutmann. The network helps show where Michael U. Gutmann may publish in the future.

Co-authorship network of co-authors of Michael U. Gutmann

This figure shows the co-authorship network connecting the top 25 collaborators of Michael U. Gutmann. A scholar is included among the top collaborators of Michael U. Gutmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael U. Gutmann. Michael U. Gutmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Designing optimal behavioral experiments using machine learning 2024 ·eLife ·(unknown), (unknown), Neil R Bramley, Peggy Seriès, Michael U. Gutmann, Christopher G. Lucas	2
2	Systematic comparison of ranking aggregation methods for gene lists in experimental results 2022 ·Bioinformatics ·Bo Wang, Andy Law, Tim Regan, Nick Parkinson, Joby Cole, Clark D Russell, David H. Dockrell, Michael U. Gutmann, J. Kenneth Baillie	6
3	Bayesian Experimental Design for Intractable Models of Cognition 2021 ·eScholarship (California Digital Library) ·(unknown), (unknown), Neil R Bramley, Michael U. Gutmann, (unknown)	1
4	Parallel Gaussian process surrogate method to accelerate likelihood-free inference 2019 ·arXiv (Cornell University) ·Marko Järvenpää, Michael U. Gutmann, Aki Vehtari, Pekka Marttinen	1
5	Weak Epistasis May Drive Adaptation in Recombining Bacteria 2018 ·Genetics ·Brian Arnold, Michael U. Gutmann, Yonatan H. Grad, Samuel K. Sheppard, Jukka Corander, Marc Lipsitch, William P. Hanage	37
6	VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning 2017 ·Edinburgh Research Explorer (University of Edinburgh) ·Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton	96
7	Bayesian inference of physiologically meaningful parameters from body sway measurements 2017 ·Scientific Reports ·(unknown), Michael U. Gutmann, Esko Keski-Vakkuri, Jukka Corander, Edward Hæggström	7
8	Frequency-dependent selection in vaccine-associated pneumococcal population dynamics 2017 ·Nature Ecology & Evolution ·Jukka Corander, Christophe Fraser, Michael U. Gutmann, Brian Arnold, William P. Hanage, Stephen D. Bentley, Marc Lipsitch, Nicholas J. Croucher	74
9	ELFI: Engine for Likelihood-Free Inference 2017 ·Journal of Machine Learning Research ·(unknown), Henri Vuollekoski, (unknown), (unknown), Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski	10
10	On the Identifiability of Transmission Dynamic Models for Infectious Diseases 2016 ·Genetics ·(unknown), Michael U. Gutmann, Samuel Kaski, Jukka Corander	14
11	Bayesian optimization for likelihood-free inference of simulator-based statistical models 2016 ·Journal of Machine Learning Research ·Michael U. Gutmann, Jukka Corander	97
12	Likelihood-free inference by penalised logistic regression 2016 ·arXiv (Cornell University) ·Ritabrata Dutta, Jukka Corander, Samuel Kaski, Michael U. Gutmann	4
13	The impact of host metapopulation structure on the population genetics of colonizing bacteria 2016 ·Journal of Theoretical Biology ·Elina Numminen, Michael U. Gutmann, Mikhail Shubin, Pekka Marttinen, Guillaume Méric, Willem van Schaik, Teresa M. Coque, Fernando Baquero, Rob J. L. Willems, Samuel K. Sheppard, Edward J. Feil, William P. Hanage, Jukka Corander	11
14	Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations 2014 ·Journal of Machine Learning Research ·Hiroaki Sasaki, Hayaru Shouno, Michael U. Gutmann, Aapo Hyvärinen	1
15	Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images 2014 ·PLoS ONE ·Michael U. Gutmann, Valero Laparra, Aapo Hyvärinen, Jesús Malo	15
16	Learning a selectivity--invariance--selectivity feature extraction architecture for images 2012 ·Edinburgh Research Explorer (University of Edinburgh) ·Michael U. Gutmann, Aapo Hyvärinen	2
17	Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics 2012 ·Journal of Machine Learning Research ·Michael U. Gutmann, Aapo Hyvärinen	313
18	Topographic Analysis of Correlated Components 2012 ·Edinburgh Research Explorer (University of Edinburgh) ·Hiroaki Sasaki, Michael U. Gutmann, Hayaru Shouno, Aapo Hyvärinen	1
19	Learning reconstruction and prediction of natural stimuli by a population of spiking neurons 2009 ·Edinburgh Research Explorer (University of Edinburgh) ·Michael U. Gutmann, Aapo Hyvärinen	0
20	Freedom through a single switch: coping and communicating with artificial ventilation 1996 ·Journal of the Neurological Sciences ·(unknown), (unknown), Michael U. Gutmann, (unknown)	8

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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