Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal
Transport Loss

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Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss

19 February 2024

Florence dÁlché-Buc

Charlotte Laclau

Matthieu Labeau

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Papers citing "Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss"

18 / 18 papers shown

Title
Synthetic Data for Blood Vessel Network Extraction Joël Mathys Andreas Plesner Jorel Elmiger Roger Wattenhofer MedIm 86 0 0 16 Apr 2025
Knowledge Graph Generation From Text Igor Melnyk Pierre Dognin Payel Das 60 25 0 18 Nov 2022
Aligning individual brains with Fused Unbalanced Gromov-Wasserstein Alexis Thual Huy Tran Tatiana Zemskova Nicolas Courty Rémi Flamary S. Dehaene Bertrand Thirion OT 54 29 0 19 Jun 2022
Relationformer: A Unified Framework for Image-to-Graph Generation Suprosanna Shit Rajat Koner Bastian Wittmann Johannes C. Paetzold Ivan Ezhov ... Jia Pan Sahand Sharifzadeh Georgios Kaissis Volker Tresp Bjoern Menze ViT 68 61 0 19 Mar 2022
A Comprehensive Survey of Scene Graphs: Generation and Application Xiaojun Chang Pengzhen Ren Pengfei Xu Zhihui Li Xiaojiang Chen Alexander G. Hauptmann 3DV 98 235 0 17 Mar 2021
Energy-Based Learning for Scene Graph Generation M. Suhail Abhay Mittal Behjat Siddiquie Chris Broaddus J. Eledath Gérard Medioni Leonid Sigal 86 165 0 03 Mar 2021
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation Thibault Séjourné François-Xavier Vialard Gabriel Peyré OT 83 71 0 09 Sep 2020
End-to-End Object Detection with Transformers Nicolas Carion Francisco Massa Gabriel Synnaeve Nicolas Usunier Alexander Kirillov Sergey Zagoruyko ViT 3DV PINN 442 13,130 0 26 May 2020
On Layer Normalization in the Transformer Architecture Ruibin Xiong Yunchang Yang Di He Kai Zheng Shuxin Zheng Chen Xing Huishuai Zhang Yanyan Lan Liwei Wang Tie-Yan Liu AI4CE 153 996 0 12 Feb 2020
Diffusion Improves Graph Learning Johannes Klicpera Stefan Weißenberger Stephan Günnemann GNN 157 712 0 28 Oct 2019
A Two-Step Graph Convolutional Decoder for Molecule Generation Xavier Bresson T. Laurent 69 61 0 08 Jun 2019
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties David Tellez G. Litjens J. A. van der Laak R. Tavenard F. Ciompi OT 89 129 0 07 Nov 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 259 7,705 0 01 Oct 2018
Optimal Transport for structured data with application on graphs Titouan Vayer Laetitia Chapel Rémi Flamary R. Tavenard Nicolas Courty OT 73 274 0 23 May 2018
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders M. Simonovsky N. Komodakis GNN BDL 123 856 0 09 Feb 2018
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 429 2,480 0 10 Mar 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 343 1,838 0 02 Mar 2017
Graph matching: relax or not? Y. Aflalo A. Bronstein Ron Kimmel 73 16 0 29 Jan 2014

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