Claire Donnat

Orcid: 0000-0001-7079-8060

According to our database1, Claire Donnat authored at least 15 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Studying the Effect of GNN Spatial Convolutions On The Embedding Space's Geometry.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Simplified Framework for Contrastive Learning for Node Representations.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Tuning the Geometry of Graph Neural Networks.
CoRR, 2022

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results.
CoRR, 2022

Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy.
CoRR, 2022


2020
Geomstats: A Python Package for Riemannian Geometry in Machine Learning.
CoRR, 2020

Introduction to Geometric Learning in Python with Geomstats.
Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

Proceedings of the Machine Learning for Health Workshop, 2020

2019
Convex Hierarchical Clustering for Graph-Structured Data.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
geomstats: a Python Package for Riemannian Geometry in Machine Learning.
CoRR, 2018

Tracking Network Dynamics: a review of distances and similarity metrics.
CoRR, 2018

Learning Structural Node Embeddings via Diffusion Wavelets.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017
Spectral Graph Wavelets for Structural Role Similarity in Networks.
CoRR, 2017

2016
A divide-and-conquer framework for large-scale subspace clustering.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016


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