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06/06/2023
Explainable AI using expressive Boolean formulas
We propose and implement an interpretable machine learning classificatio...
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02/03/2023
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set
We provide a comprehensive reply to the comment written by Chiara Angeli...
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06/08/2022
Optimization of Robot Trajectory Planning with Nature-Inspired and Hybrid Quantum Algorithms
We solve robot trajectory planning problems at industry-relevant scales....
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02/03/2022
Graph Coloring with Physics-Inspired Graph Neural Networks
We show how graph neural networks can be used to solve the canonical gra...
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07/02/2021
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
We demonstrate how graph neural networks can be used to solve combinator...
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05/28/2020
Chook – A comprehensive suite for generating binary optimization problems with planted solutions
We present Chook, an open-source Python-based tool to generate discrete ...
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06/14/2019
A feasibility pump algorithm embedded in an annealing framework
The feasibility pump algorithm is an efficient primal heuristic for find...
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06/22/2018
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
The Fujitsu Digital Annealer (DA) is designed to solve fully connected q...
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06/22/2018
Physics-inspired optimization for constraint-satisfaction problems using a digital annealer
The Fujitsu Digital Annealer is designed to solve fully-connected quadra...
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01/18/2018
NAE-SAT-based probabilistic membership filters
Probabilistic membership filters are a type of data structure designed t...
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10/25/2017
Optimization of population annealing Monte Carlo for large-scale spin-glass simulations
Population annealing Monte Carlo is an efficient sequential algorithm fo...
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08/17/2016
Evolutionary Approaches to Optimization Problems in Chimera Topologies
Chimera graphs define the topology of one of the first commercially avai...
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11/30/2012
