Nina Miolane

Nina Miolane

Stanford University

H-index: 11

North America-United States

About Nina Miolane

Nina Miolane, With an exceptional h-index of 11 and a recent h-index of 11 (since 2020), a distinguished researcher at Stanford University, specializes in the field of geometric artificial intelligence, shape analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

An efficient algorithm for the Riemannian logarithm on the Stiefel manifold for a family of Riemannian metrics

Position Paper: Challenges and Opportunities in Topological Deep Learning

A General Framework for Robust G-Invariance in G-Equivariant Networks

TopoX: a suite of Python packages for machine learning on topological domains

Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations

Architectures of topological deep learning: A survey on topological neural networks

Evaluation of Representational Similarity Scores Across Human Visual Cortex

Septins regulate border cell surface geometry, shape, and motility downstream of Rho in Drosophila

Nina Miolane Information

University

Position

Postdoctoral Researcher at

Citations(all)

433

Citations(since 2020)

395

Cited By

128

hIndex(all)

11

hIndex(since 2020)

11

i10Index(all)

15

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Nina Miolane Skills & Research Interests

geometric artificial intelligence

shape analysis

Top articles of Nina Miolane

Title

Journal

Author(s)

Publication Date

An efficient algorithm for the Riemannian logarithm on the Stiefel manifold for a family of Riemannian metrics

arXiv preprint arXiv:2403.11730

Simon Mataigne

Ralf Zimmermann

Nina Miolane

2024/3/18

Position Paper: Challenges and Opportunities in Topological Deep Learning

Theodore Papamarkou

Tolga Birdal

Michael Bronstein

Gunnar Carlsson

Justin Curry

...

2024/2/14

A General Framework for Robust G-Invariance in G-Equivariant Networks

Neural Information Processing Systems (NeurIPS)

Sophia Sanborn

Nina Miolane

2023

TopoX: a suite of Python packages for machine learning on topological domains

arXiv preprint arXiv:2402.02441

Mustafa Hajij

Mathilde Papillon

Florian Frantzen

Jens Agerberg

Ibrahem AlJabea

...

2024/2/4

Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations

bioRxiv

David Alexander Klindt

Aapo Hyvarinen

Axel Levy

Nina Miolane

Frederic Poitevin

2024

Architectures of topological deep learning: A survey on topological neural networks

arXiv preprint arXiv:2304.10031

Mathilde Papillon

Sophia Sanborn

Mustafa Hajij

Nina Miolane

2023/4/20

Evaluation of Representational Similarity Scores Across Human Visual Cortex

Francisco Acosta

Colin Conwell

Sophia Sanborn

David A Klindt

Nina Miolane

2023/12/18

Septins regulate border cell surface geometry, shape, and motility downstream of Rho in Drosophila

Developmental cell

Allison M Gabbert

Joseph P Campanale

James A Mondo

Noah P Mitchell

Adele Myers

...

2023/8/7

Multimodal Cell Complex Neural Networks for Prediction of Multiple Drug Side Effects Severity and Frequency

2023/3/23

Parametric information geometry with the package Geomstats

ACM Transactions on Mathematical Software

Alice Le Brigant

Jules Deschamps

Antoine Collas

Nina Miolane

2023/12/15

Group equivariant sparse coding

Christian Shewmake

Nina Miolane

Bruno Olshausen

2023/8/1

Introduction to riemannian geometry and geometric statistics: from basic theory to implementation with geomstats

Foundations and Trends® in Machine Learning

Nicolas Guigui

Nina Miolane

Xavier Pennec

2023/2/21

Visual Scene Representation with Hierarchical Equivariant Sparse Coding

Christian A Shewmake

Domas Buracas

Hansen Lillemark

Jinho Shin

Erik J Bekkers

...

2023/11/29

Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation

Adele Myers

Caitlin Taylor

Emily Jacobs

Nina Miolane

2023

Using a Riemannian elastic metric for statistical analysis of tumor cell shape heterogeneity

bioRxiv

Wanxin Li

Ashok Prasad

Nina Miolane

Khanh Dao Duc

2023

Identifying Interpretable Visual Features in Artificial and Biological Neural Systems

arXiv preprint arXiv:2310.11431

David Klindt

Sophia Sanborn

Francisco Acosta

Frédéric Poitevin

Nina Miolane

2023/10/17

Quantifying extrinsic curvature in neural manifolds

Francisco Acosta

Sophia Sanborn

Khanh Dao Duc

Manu Madhav

Nina Miolane

2023

Reconstructing Heterogeneous Cryo-EM Molecular Structures by Decomposing Them into Polymer Chains

arXiv preprint arXiv:2306.07274

Bongjin Koo

Julien Martel

Ariana Peck

Axel Levy

Frédéric Poitevin

...

2023/6/12

Icml 2023 topological deep learning challenge: Design and results

Mathilde Papillon

Mustafa Hajij

Audun Myers

Florianand Frantzen

Ghada Zamzmi

...

2023/9/27

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

bioRxiv

Wanxin Li

Jules Mirone

Ashok Prasad

Nina Miolane

Carine Legrand

...

2023/2/15

See List of Professors in Nina Miolane University(Stanford University)

Co-Authors

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