Learning signals defined on graphs with optimal transport and Gaussian process regression

21 October 2024

Raphael Carpintero Perez

Papers citing "Learning signals defined on graphs with optimal transport and Gaussian process regression"

32 / 32 papers shown

Title
Bayesian neural networks for predicting uncertainty in full-field material response G. Pasparakis Lori Graham-Brady Michael D. Shields AI4CE 69 4 0 21 Jun 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 60 4 0 06 Feb 2024
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees Edgar Jaber Vincent Blot Nicolas Brunel V. Chabridon Emmanuel Remy Bertrand Iooss Didier Lucor Mathilde Mougeot Alessandro Leite 60 8 0 15 Jan 2024
Recent Advances in Optimal Transport for Machine Learning Eduardo Fernandes Montesuma Fred-Maurice Ngole-Mboula Antoine Souloumiac OOD OT 37 34 0 28 Jun 2023
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability F. Casenave B. Staber Xavier Roynard AI4CE 53 15 0 22 May 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 51 8 0 12 Oct 2022
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zong-Yi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar AI4CE 142 264 0 11 Jul 2022
Template based Graph Neural Network with Optimal Transport Distances Cédric Vincent-Cuaz Rémi Flamary Marco Corneli Titouan Vayer Nicolas Courty OT 60 20 0 31 May 2022
Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim Joshua Robinson Lingxiao Zhao Tess E. Smidt S. Sra Haggai Maron Stefanie Jegelka 63 143 0 25 Feb 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 40 41 0 09 Feb 2022
Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein Marco Cuturi Laetitia Meng-Papaxanthos Yingtao Tian Charlotte Bunne Geoff Davis O. Teboul OT 165 98 0 28 Jan 2022
Accurate Point Cloud Registration with Robust Optimal Transport Zhengyang Shen Jean Feydy Peirong Liu A. Curiale R. S. J. Estépar Raúl San José Estépar Marc Niethammer 3DPC OOD OT 25 53 0 01 Nov 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 382 2,355 0 18 Oct 2020
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 41 761 0 07 Oct 2020
Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and a Path to Best Practices for Machine Learning in Chemistry G. Vishwakarma Aditya Sonpal J. Hachmann 72 48 0 30 Sep 2020
Graph signal processing for machine learning: A review and new perspectives Xiaowen Dong D. Thanou Laura Toni M. Bronstein P. Frossard 38 157 0 31 Jul 2020
Gaussian Processes on Graphs via Spectral Kernel Learning Yin-Cong Zhi Yin Cheng Ng Xiaowen Dong 17 32 0 12 Jun 2020
Wasserstein Weisfeiler-Lehman Graph Kernels Matteo Togninalli M. Ghisu Felipe Llinares-López Bastian Rieck Karsten Borgwardt 50 196 0 04 Jun 2019
Graph Kernels: A Survey Giannis Nikolentzos Giannis Siglidis Michalis Vazirgiannis 98 123 0 27 Apr 2019
A Survey on Graph Kernels Nils M. Kriege Fredrik D. Johansson Christopher Morris 107 416 0 28 Mar 2019
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 339 3,101 0 04 Jun 2018
Optimal Transport for structured data with application on graphs Titouan Vayer Laetitia Chapel Rémi Flamary R. Tavenard Nicolas Courty OT 48 270 0 23 May 2018
Gaussian Processes Over Graphs Arun Venkitaraman Saikat Chatterjee P. Händel 25 39 0 15 Mar 2018
Joint Distribution Optimal Transportation for Domain Adaptation Nicolas Courty Rémi Flamary Amaury Habrard A. Rakotomamonjy OT OOD 66 561 0 24 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 239 7,388 0 04 Apr 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 400 28,795 0 09 Sep 2016
Operator-valued Kernels for Learning from Functional Response Data Hachem Kadri E. Duflos Philippe Preux S. Canu A. Rakotomamonjy Julien Audiffren 46 128 0 28 Oct 2015
Optimal Transport for Domain Adaptation Nicolas Courty Rémi Flamary D. Tuia A. Rakotomamonjy OT OOD 53 1,112 0 02 Jul 2015
The Emerging Field of Signal Processing on Graphs: Extending High-Dimensional Data Analysis to Networks and Other Irregular Domains D. Shuman S. K. Narang P. Frossard Antonio Ortega P. Vandergheynst 84 3,962 0 31 Oct 2012
Equivalence of distance-based and RKHS-based statistics in hypothesis testing Dino Sejdinovic Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu 103 681 0 25 Jul 2012
A Generalized Kernel Approach to Structured Output Learning Hachem Kadri Mohammad Ghavamzadeh Philippe Preux 87 37 0 10 May 2012
Kernels for Vector-Valued Functions: a Review Mauricio A. Alvarez Lorenzo Rosasco Neil D. Lawrence GP 102 918 0 30 Jun 2011