Michael Eickenberg

4.5k total citations · 1 hit paper
35 papers, 2.1k citations indexed

About

Michael Eickenberg is a scholar working on Astronomy and Astrophysics, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Michael Eickenberg has authored 35 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Astronomy and Astrophysics, 9 papers in Cognitive Neuroscience and 8 papers in Artificial Intelligence. Recurrent topics in Michael Eickenberg's work include Galaxies: Formation, Evolution, Phenomena (10 papers), Neural dynamics and brain function (5 papers) and Functional Brain Connectivity Studies (5 papers). Michael Eickenberg is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (10 papers), Neural dynamics and brain function (5 papers) and Functional Brain Connectivity Studies (5 papers). Michael Eickenberg collaborates with scholars based in United States, Canada and France. Michael Eickenberg's co-authors include Bertrand Thirion, Gaël Varoquaux, Alexandre Gramfort, Fabian Pedregosa, Philippe Gervais, Jean Kossaifi, Andreas Mueller, Alexandre Abraham, Shirley Ho and Bruno Régaldo-Saint Blancard and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and Applied Physics Letters.

In The Last Decade

Michael Eickenberg

34 papers receiving 2.0k 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.

Machine learning for neuroimaging with scikit-learn

2014 1.4k citations Michael Eickenberg, Alexandre Gramfort et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Eickenberg United States	16	1.0k	343	217	180	178	35	2.1k
Andreas Mueller Austria	14	1.1k 1.1×	300 0.9×	266 1.2×	32 0.2×	212 1.2×	44	2.5k
Kevin H. Knuth United States	18	1.3k 1.3×	78 0.2×	273 1.3×	105 0.6×	102 0.6×	98	2.2k
Shu Zhang China	24	1.1k 1.0×	589 1.7×	161 0.7×	140 0.8×	54 0.3×	124	1.8k
Seunghwan Kim South Korea	40	1.3k 1.2×	207 0.6×	129 0.6×	24 0.1×	557 3.1×	238	5.0k
Steven B. Lowen United States	31	1.2k 1.1×	146 0.4×	213 1.0×	28 0.2×	372 2.1×	68	3.1k
Masa-aki Sato Japan	25	1.2k 1.1×	257 0.7×	819 3.8×	45 0.3×	356 2.0×	113	3.2k
Lingxiao Wang China	26	182 0.2×	83 0.2×	295 1.4×	113 0.6×	144 0.8×	132	2.0k
Vanessa Sochat United States	10	589 0.6×	205 0.6×	99 0.5×	27 0.1×	355 2.0×	32	1.6k
Joseph T. Lizier Australia	35	1.8k 1.7×	109 0.3×	678 3.1×	44 0.2×	390 2.2×	90	3.8k
Vincent Barra France	24	166 0.2×	214 0.6×	169 0.8×	76 0.4×	167 0.9×	85	1.8k

Countries citing papers authored by Michael Eickenberg

Since Specialization

Citations

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

Fields of papers citing papers by Michael Eickenberg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Eickenberg

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Eickenberg. A scholar is included among the top collaborators of Michael Eickenberg 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 Eickenberg. Michael Eickenberg 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

Eickenberg, Michael, et al.. (2025). Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 72(5). 601–611. 1 indexed citations

Parker, Liam, François Lanusse, Siavash Golkar, et al.. (2024). AstroCLIP: a cross-modal foundation model for galaxies. Monthly Notices of the Royal Astronomical Society. 531(4). 4990–5011. 19 indexed citations

Eickenberg, Michael, et al.. (2024). Adversarial Attacks on the Interpretation of Neuron Activation Maximization. Proceedings of the AAAI Conference on Artificial Intelligence. 38(5). 4315–4324.

Hahn, ChangHoon, Pablo Lemos, Liam Parker, et al.. (2024). Cosmological constraints from non-Gaussian and nonlinear galaxy clustering using the SimBIG inference framework. Nature Astronomy. 8(11). 1457–1467. 11 indexed citations

Blancard, Bruno Régaldo-Saint, ChangHoon Hahn, Shirley Ho, et al.. (2024). Galaxy clustering analysis with SimBIG and the wavelet scattering transform. Physical review. D. 109(8). 21 indexed citations

Hahn, ChangHoon, Michael Eickenberg, Shirley Ho, et al.. (2024). Cosmological constraints from the nonlinear galaxy bispectrum. Physical review. D. 109(8). 18 indexed citations

Lemos, Pablo, Liam Parker, ChangHoon Hahn, et al.. (2024). Field-level simulation-based inference of galaxy clustering with convolutional neural networks. Physical review. D. 109(8). 26 indexed citations

Lemos, Pablo, Miles Cranmer, ChangHoon Hahn, et al.. (2023). Robust simulation-based inference in cosmology with Bayesian neural networks. Machine Learning Science and Technology. 4(1). 01LT01–01LT01. 21 indexed citations

Massara, Elena, Francisco Villaescusa-Navarro, ChangHoon Hahn, et al.. (2023). Cosmological Information in the Marked Power Spectrum of the Galaxy Field. The Astrophysical Journal. 951(1). 70–70. 26 indexed citations

10.

Blancard, Bruno Régaldo-Saint, Erwan Allys, F. Boulanger, et al.. (2023). Generative Models of Multichannel Data from a Single Example—Application to Dust Emission. The Astrophysical Journal. 943(1). 9–9. 7 indexed citations

11.

Hahn, ChangHoon, Michael Eickenberg, Shirley Ho, et al.. (2023). SimBIG: mock challenge for a forward modeling approach to galaxy clustering. Journal of Cosmology and Astroparticle Physics. 2023(4). 10–10. 26 indexed citations

12.

Benkarim, Oualid, Casey Paquola, Bo‐yong Park, et al.. (2022). Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging. PLoS Biology. 20(4). e3001627–e3001627. 26 indexed citations

13.

Warrick, Philip, Vincent Lostanlen, Michael Eickenberg, et al.. (2022). Arrhythmia classification of 12-lead and reduced-lead electrocardiograms via recurrent networks, scattering, and phase harmonic correlation. Physiological Measurement. 43(9). 94002–94002. 4 indexed citations

14.

Belilovsky, Eugene, Michael Eickenberg, & Edouard Oyallon. (2018). Shallow Learning For Deep Networks. 1 indexed citations

15.

Eickenberg, Michael, Gaël Varoquaux, Bertrand Thirion, & Alexandre Gramfort. (2017). Convolutional Network Layers Map the Function of the Human Visual Cortex.. ERCIM news/ERCIM news online edition. 2017. 2 indexed citations

16.

Eickenberg, Michael, et al.. (2017). Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. Neural Information Processing Systems. 30. 6540–6549. 11 indexed citations

17.

Bzdok, Danilo, Michael Eickenberg, Gaël Varoquaux, & Bertrand Thirion. (2017). Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. Lecture notes in computer science. 10265. 323–335. 7 indexed citations

18.

Eickenberg, Michael, Alexandre Gramfort, Gaël Varoquaux, & Bertrand Thirion. (2016). Seeing it all: Convolutional network layers map the function of the human visual system. NeuroImage. 152. 184–194. 180 indexed citations

19.

Bzdok, Danilo, Gaël Varoquaux, Olivier Grisel, et al.. (2016). Formal Models of the Network Co-occurrence Underlying Mental Operations. PLoS Computational Biology. 12(6). e1004994–e1004994. 51 indexed citations

20.

Pedregosa, Fabián, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, & Alexandre Gramfort. (2014). Data-driven HRF estimation for encoding and decoding models. NeuroImage. 104. 209–220. 45 indexed citations

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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