Martin Heusel

9.5k total citations · 1 hit paper
6 papers, 2.5k citations indexed

About

Martin Heusel is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Martin Heusel has authored 6 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Artificial Intelligence. Recurrent topics in Martin Heusel's work include Generative Adversarial Networks and Image Synthesis (2 papers), Gene expression and cancer classification (2 papers) and Machine Learning in Bioinformatics (1 paper). Martin Heusel is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (2 papers), Gene expression and cancer classification (2 papers) and Machine Learning in Bioinformatics (1 paper). Martin Heusel collaborates with scholars based in Austria, Germany and Belgium. Martin Heusel's co-authors include Sepp Hochreiter, Thomas Unterthiner, Bernhard Nessler, Hubert Ramsauer, Andreas Mayr, Klaus Obermayer, Hinrich W. H. Göhlmann, Dan Lin, Ziv Shkedy and Adetayo Kasim and has published in prestigious journals such as Bioinformatics, arXiv (Cornell University) and International Conference on Learning Representations.

In The Last Decade

Martin Heusel

6 papers receiving 2.4k 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.

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

2017 2.0k citations Martin Heusel, Hubert Ramsauer et al. arXiv (Cornell University) profile →

Peers

Countries citing papers authored by Martin Heusel

Since Specialization

Citations

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

Fields of papers citing papers by Martin Heusel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Heusel. 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 Martin Heusel. The network helps show where Martin Heusel may publish in the future.

Co-authorship network of co-authors of Martin Heusel

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Heusel. A scholar is included among the top collaborators of Martin Heusel 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 Martin Heusel. Martin Heusel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

#	Work	Indexed citations
1	Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields 2018 ·International Conference on Learning Representations ·Thomas Unterthiner, Bernhard Nessler, (unknown), Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter	6
2	GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium breakdown → 2017 ·arXiv (Cornell University) ·Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter	1986
3	Speeding up Semantic Segmentation for Autonomous Driving 2016 ·(unknown), Jose A. Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, (unknown), (unknown), Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Bernhard Nessler, Sepp Hochreiter	165
4	FABIA: factor analysis for bicluster acquisition 2010 ·Bioinformatics ·Sepp Hochreiter, Ulrich Bodenhofer, Martin Heusel, Andreas Mayr, Andreas Mitterecker, Adetayo Kasim, Tatsiana Khamiakova, Suzy Van Sanden, Dan Lin, Willem Talloen, Luc Bijnens, Hinrich W. H. Göhlmann, Ziv Shkedy, Djork-Arné Clevert	206
5	FABIA: factor analysis for bicluster acquisition 2010 ·Sepp Hochreiter, Ulrich Bodenhofer, Martin Heusel, Andreas Mayr, Andreas Mitterecker, Adetayo Kasim, Tatsiana Khamiakova, Suzy Van Sanden, Dan Lin, Willem Talloen, Luc Bijnens, Hinrich W. H. Göhlmann, Ziv Shkedy, Djork-Arné Clevert	57
6	Fast model-based protein homology detection without alignment 2007 ·Bioinformatics ·Sepp Hochreiter, Martin Heusel, Klaus Obermayer	81

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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