Claire Donnat

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 18

Top Topics

Computational Geometry

Network Dynamics

Structured Data

Similarity Metrics

Top Venues

Publications

Jihee You, Sowon Jeong, Claire Donnat
GNUMAP: A Parameter-Free Approach to Unsupervised Dimensionality Reduction via Graph Neural Networks. CoRR (2024)
Ilgee Hong, Huy Tran, Claire Donnat
A Simplified Framework for Contrastive Learning for Node Representations. CoRR (2023)
Claire Donnat, Sowon Jeong
Studying the Effect of GNN Spatial Convolutions On The Embedding Space's Geometry. UAI (2023)
Ilgee Hong, Huy Tran, Claire Donnat
A Simplified Framework for Contrastive Learning for Node Representations. ACSSC (2023)
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava Yazdani, Christoph von Tycowicz, Nina Miolane
ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR (2022)
Claire Donnat, Axel Levy, Frédéric Poitevin, Nina Miolane
Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy. CoRR (2022)
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML (2022)
Sowon Jeong, Claire Donnat
Tuning the Geometry of Graph Neural Networks. CoRR (2022)
Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec
Introduction to Geometric Learning in Python with Geomstats. SciPy (2020)
Claire Donnat, Nina Miolane, Freddy Bunbury, Jack Kreindler
A {B. ML4H@NeurIPS (2020)
Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec
Geomstats: A Python Package for Riemannian Geometry in Machine Learning. CoRR (2020)
Claire Donnat, Susan P. Holmes
Convex Hierarchical Clustering for Graph-Structured Data. CoRR (2019)
Claire Donnat, Susan P. Holmes
Convex Hierarchical Clustering for Graph-Structured Data. ACSSC (2019)
Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, Xavier Pennec
geomstats: a Python Package for Riemannian Geometry in Machine Learning. CoRR (2018)
Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec
Learning Structural Node Embeddings via Diffusion Wavelets. KDD (2018)
Claire Donnat, Susan P. Holmes
Tracking Network Dynamics: a review of distances and similarity metrics. CoRR (2018)
Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec
Spectral Graph Wavelets for Structural Role Similarity in Networks. CoRR (2017)
Chong You, Claire Donnat, Daniel P. Robinson, René Vidal
A divide-and-conquer framework for large-scale subspace clustering. ACSSC (2016)