Jannis Schuecker

954 total citations · 1 hit paper
7 papers, 548 citations indexed

About

Jannis Schuecker is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications. According to data from OpenAlex, Jannis Schuecker has authored 7 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistical and Nonlinear Physics, 4 papers in Cognitive Neuroscience and 2 papers in Computer Networks and Communications. Recurrent topics in Jannis Schuecker's work include Neural dynamics and brain function (4 papers), stochastic dynamics and bifurcation (4 papers) and Neural Networks and Applications (2 papers). Jannis Schuecker is often cited by papers focused on Neural dynamics and brain function (4 papers), stochastic dynamics and bifurcation (4 papers) and Neural Networks and Applications (2 papers). Jannis Schuecker collaborates with scholars based in Germany, Norway and Switzerland. Jannis Schuecker's co-authors include Sven Giesselbach, Birgit Kirsch, Rajkumar Ramamurthy, Laura von Rueden, Julius Pfrommer, Bogdan Georgiev, Sebastian Mayer, Katharina Beckh, Raoul Heese and Michał Walczak and has published in prestigious journals such as PLoS Computational Biology, IEEE Transactions on Knowledge and Data Engineering and BMC Neuroscience.

In The Last Decade

Jannis Schuecker

6 papers receiving 527 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.

Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems

2021 469 citations Laura von Rueden, Sebastian Mayer et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers

Countries citing papers authored by Jannis Schuecker

Since Specialization

Citations

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

Fields of papers citing papers by Jannis Schuecker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jannis Schuecker

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

All Works

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7 of 7 papers shown

#	Work	Indexed citations
1	Learning Deep Generative Models for Queuing Systems 2021 ·Proceedings of the AAAI Conference on Artificial Intelligence ·(unknown), (unknown), (unknown), Christian Bauckhage, Jannis Schuecker, (unknown)	4
2	Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems breakdown → 2021 ·IEEE Transactions on Knowledge and Data Engineering ·Laura von Rueden, Sebastian Mayer, Katharina Beckh, Bogdan Georgiev, Sven Giesselbach, Raoul Heese, Birgit Kirsch, Michał Walczak, Julius Pfrommer, (unknown), Rajkumar Ramamurthy, Jochen Garcke, Christian Bauckhage, Jannis Schuecker	469
3	Conditions for wave trains in spiking neural networks 2020 ·Physical Review Research ·Johanna Senk, (unknown), Jannis Schuecker, Espen Hagen, Tom Tetzlaff, Markus Diesmann, Moritz Helias	16
4	Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome 2017 ·PLoS Computational Biology ·Jannis Schuecker, Maximilian Schmidt, Sacha J. van Albada, Markus Diesmann, Moritz Helias	16
5	NEST 2.8.0 2015 ·Zenodo (CERN European Organization for Nuclear Research) ·Jochen Martin Eppler, (unknown), Alexander Peyser, (unknown), Abigail Morrison, (unknown), (unknown), (unknown), (unknown), (unknown), Susanne Kunkel, Jakob Jordan, (unknown), (unknown), Jannis Schuecker, (unknown), (unknown), Moritz Deger, Jesús A. Garrido, (unknown), (unknown), Luis F. Riquelme, (unknown), (unknown), (unknown), Hans Ekkehard Pleßer	17
6	Modulated escape from a metastable state driven by colored noise 2015 ·Physical Review E ·Jannis Schuecker, Markus Diesmann, Moritz Helias	26
7	The transfer function of the LIF model: from white to filtered noise 2014 ·BMC Neuroscience ·Jannis Schuecker, Markus Diesmann, Moritz Helias	0

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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