Graph Neural Networks for Maximum Constraint Satisfaction

Graph Neural Networks for Maximum Constraint Satisfaction

18 September 2019

Papers citing "Graph Neural Networks for Maximum Constraint Satisfaction"

10 / 10 papers shown

Title
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 27 8 0 15 Nov 2023
Unveiling the Limits of Learned Local Search Heuristics: Are You the Mightiest of the Meek? Ankur Nath Alan Kuhnle 19 0 0 30 Oct 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets Dinghuai Zhang H. Dai Nikolay Malkin Aaron Courville Yoshua Bengio L. Pan 24 36 0 26 May 2023
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning Joaquim Ortiz de Haro Jung-Su Ha Danny Driess E. Karpas Marc Toussaint 21 2 0 22 Oct 2022
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction Jan Tonshoff Berke Kisin Jakob Lindner Martin Grohe GNN 16 22 0 22 Aug 2022
Solving AC Power Flow with Graph Neural Networks under Realistic Constraints Luis Bottcher Hinrikus Wolf Bastian Jung Philipp Lutat M. Trageser Oliver Pohl Andreas Ulbig Martin Grohe 13 10 0 14 Apr 2022
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits Simon Ståhlberg Blai Bonet Hector Geffner 27 48 0 21 Sep 2021
Link Scheduling using Graph Neural Networks Zhongyuan Zhao Gunjan Verma Chirag R. Rao A. Swami Santiago Segarra GNN 21 33 0 12 Sep 2021
The Logic of Graph Neural Networks Martin Grohe AI4CE 13 87 0 29 Apr 2021
word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data Martin Grohe 27 170 0 27 Mar 2020