Ludwig-Maximilians-Universität München
UniversityMunich, Germany
The most-cited papers from Ludwig-Maximilians-Universität München (Germany) in the NobleBlocks index. Counts are from our index (snapshot, October 2026) and are lower bounds: author affiliations are linked for part of the index.
Linked papers (our index)
658
Author profiles (our index)
893
Established (ROR)
1472
Also known as
LMU MünchenLudwig Maximilian University of MunichLudwig-Maximilians-Universität in MunichUniversity of MunichUniversität MünchenLMU
Top-cited papers from Ludwig-Maximilians-Universität München
From our index (snapshot, October 2026): papers with an author affiliation linked to this institution, ranked by citation count. Counts that fail a plausibility check are left out.
PLS-SEM: Indeed a Silver Bullet
Joe F. Hair, Christian M. Ringle, Marko Sarstedt
2011· The Journal of Marketing Theory and Practice20.3K
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser +1 more
2022· 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)12.4K
An assessment of the use of partial least squares structural equation modeling in marketing research
Joe F. Hair, Marko Sarstedt, Christian M. Ringle, Jeannette A. Mena
2011· Journal of the Academy of Marketing Science7.7K
The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package<sup>*</sup>
Adrian M. Price-Whelan, Brigitta Sipőcz, Hans Moritz Günther, Pey Lian Lim +2 more
2018· The Astronomical Journal6.9K
<i>Planck</i>2013 results. XVI. Cosmological parameters
P. A. R. Ade, N. Aghanim, C. Armitage-Caplan, M. Arnaud +2 more
2014· Astronomy and Astrophysics6.3K
Review of Particle Physics
J. Beringer, J-F. Arguin, R. M. Barnett, K. Copic +2 more
2012· Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology5.9K
LOF
Markus Breunig, Hans‐Peter Kriegel, Raymond T. Ng, Jörg Sander
2000· ACM SIGMOD Record5.1K
ChatGPT for good? On opportunities and challenges of large language models for education
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, Maria Bannert +2 more
2023· Learning and Individual Differences4.4K