Nina Miolane

407 total citations
18 papers, 61 citations indexed

About

Nina Miolane is a scholar working on Geometry and Topology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Nina Miolane has authored 18 papers receiving a total of 61 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Geometry and Topology, 4 papers in Artificial Intelligence and 4 papers in Computational Theory and Mathematics. Recurrent topics in Nina Miolane's work include Morphological variations and asymmetry (7 papers), Topological and Geometric Data Analysis (3 papers) and Bayesian Methods and Mixture Models (2 papers). Nina Miolane is often cited by papers focused on Morphological variations and asymmetry (7 papers), Topological and Geometric Data Analysis (3 papers) and Bayesian Methods and Mixture Models (2 papers). Nina Miolane collaborates with scholars based in United States, France and Canada. Nina Miolane's co-authors include Xavier Pennec, Frédéric Poitevin, Claire Donnat, Ellen D. Zhong, Joseph P. Campanale, Aapo Hyvärinen, Susan Holmes, Bernhard Kainz, Sebastian J. Streichan and Noah Mitchell and has published in prestigious journals such as Developmental Cell, PLoS Biology and Journal of Structural Biology.

In The Last Decade

Nina Miolane

14 papers receiving 60 citations

Peers

Nina Miolane

CVPR

SCF

Alberto Bailoni Germany

Steffen Wolf Germany

Jakob Troidl United States

C.P. O'Grady United States

Jean-Christophe Olaya Germany

Jordão Bragantini Brazil

Daniel Westphal Germany

Jackson Gorham United States

I. A. Gaponenko United States

Alberto Bailoni Germany

Nina Miolane

6 ×0.4

15 ×1.3

CVPR

12 ×1.1

0 ×0.0

3 ×0.3

SCF

Citations per year, relative to Nina Miolane Nina Miolane (= 1×) peers Alberto Bailoni

Countries citing papers authored by Nina Miolane

Since Specialization

Citations

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

Fields of papers citing papers by Nina Miolane

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Miolane

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

All Works

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18 of 18 papers shown

Pennec, Xavier, et al.. (2025). Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures. Machine Learning Science and Technology. 6(3). 31002–31002. 2 indexed citations

Miolane, Nina. (2025). The fifth era of science: Artificial scientific intelligence. PLoS Biology. 23(6). e3003230–e3003230. 1 indexed citations

Zimmermann, Ralf, et al.. (2025). An Efficient Algorithm for the Riemannian Logarithm on the Stiefel Manifold for a Family of Riemannian Metrics. SIAM Journal on Matrix Analysis and Applications. 46(2). 879–905.

Klindt, David, et al.. (2024). Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations. Frontiers in Molecular Biosciences. 11. 1393564–1393564. 4 indexed citations

Li, Wanxin, Ashok Prasad, Nina Miolane, & Khanh Dao Duc. (2024). Unveiling cellular morphology: statistical analysis using a Riemannian elastic metric in cancer cell image datasets. eScholarship (California Digital Library). 7(S2). 845–859.

Miolane, Nina, et al.. (2023). Parametric Information Geometry with the Package Geomstats. ACM Transactions on Mathematical Software. 49(4). 1–26. 1 indexed citations

Campanale, Joseph P., et al.. (2023). Septins regulate border cell surface geometry, shape, and motility downstream of Rho in Drosophila. Developmental Cell. 58(15). 1399–1413.e5. 7 indexed citations

Ángel-Bello, Francisco, et al.. (2023). Quantifying Extrinsic Curvature in Neural Manifolds. 9. 610–619. 2 indexed citations

Taylor, Caitlin M., et al.. (2023). Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation. 2534–2543.

10.

Miolane, Nina, et al.. (2023). Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats. HAL (Le Centre pour la Communication Scientifique Directe). 16(3). 329–493. 11 indexed citations

11.

Donnat, Claire, et al.. (2022). Deep generative modeling for volume reconstruction in cryo-electron microscopy. Journal of Structural Biology. 214(4). 107920–107920. 14 indexed citations

12.

Miolane, Nina, Benjamin Hou, Stefan Heyder, et al.. (2020). Introduction to Geometric Learning in Python with Geomstats. Proceedings of the Python in Science Conferences. 48–57. 3 indexed citations

13.

Miolane, Nina, Susan Holmes, & Xavier Pennec. (2018). Topologically Constrained Template Estimation via Morse--Smale Complexes Controls Its Statistical Consistency. HAL (Le Centre pour la Communication Scientifique Directe). 2(2). 348–375.

14.

Hou, Benjamin, Nina Miolane, Bishesh Khanal, et al.. (2018). Deep Pose Estimation for Image-Based Registration. 4 indexed citations

15.

Miolane, Nina, Susan Holmes, & Xavier Pennec. (2017). Template Shape Estimation: Correcting an Asymptotic Bias. SIAM Journal on Imaging Sciences. 10(2). 808–844. 4 indexed citations

16.

Miolane, Nina & Xavier Pennec. (2015). Computing Bi-Invariant Pseudo-Metrics on Lie Groups for Consistent Statistics. Entropy. 17(4). 1850–1881. 4 indexed citations

17.

Miolane, Nina, et al.. (2014). Analyse biométrique de l’anneau pelvien en 3 dimensions – à propos de 100 scanners. Revue de Chirurgie Orthopédique et Traumatologique. 100(7). S241–S241. 1 indexed citations

18.

Miolane, Nina, Xavier Pennec, & K.S. Stelle. (2013). Defining a mean on Lie groups. 3 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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