Computing Effective Dimension for Quantum ML Models in PyTorch

Local and global variants, Fisher estimation, epsilon-ball sampling, and log-space stability, with PennyLane code and a time-series experiment. The post Computing Effective Dimension for Quantum ML Models in PyTorch appeared first on Towards Data Science.

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Computing Effective Dimension for Quantum ML Models in PyTorch

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Computing Effective Dimension for Quantum ML Models in PyTorch

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