A tensor-network encoding of TSP tours with Boltzmann weighting and explicit constraint filters that supplies a marginal formula for optimal tours in the zero-temperature exact limit.
A quantum-inspired tensor network algorithm for constrained combinatorial optimization problems
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2023 3verdicts
UNVERDICTED 3representative citing papers
Introduces two algorithms for efficient finite initialization of tensor network layers via iterative partial norm computations, applied to MPS/TT and MPO/TT-M layers with scaling analysis and public code.
Tensor network algorithms provide exact optimal task assignments on machines under directed constraints, with preprocessing and iterative improvements to reduce complexity.
citing papers explorer
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Tensor-Network Formulation of the Traveling Salesman Problem and Variants
A tensor-network encoding of TSP tours with Boltzmann weighting and explicit constraint filters that supplies a marginal formula for optimal tours in the zero-temperature exact limit.
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Efficient Finite Initialization with Partial Norms for Tensorized Neural Networks and Tensor Networks Algorithms
Introduces two algorithms for efficient finite initialization of tensor network layers via iterative partial norm computations, applied to MPS/TT and MPO/TT-M layers with scaling analysis and public code.
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Task Scheduling Optimization with Direct Constraints from a Tensor Network Perspective
Tensor network algorithms provide exact optimal task assignments on machines under directed constraints, with preprocessing and iterative improvements to reduce complexity.