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Neural Controlled Differential Equations with Quantum Hidden Evolutions

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arxiv 2404.19673 v2 pith:4SAJT6VO submitted 2024-04-30 cs.LG

classification cs.LG
keywords controlleddifferentialneuralquantumclassificationequationequationshidden
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We introduce a class of neural controlled differential equation inspired by quantum mechanics. Neural quantum controlled differential equations (NQDEs) model the dynamics by analogue of the Schr\"{o}dinger equation. Specifically, the hidden state represents the wave function, and its collapse leads to an interpretation of the classification probability. We implement and compare the results of four variants of NQDEs on a toy spiral classification problem.

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  1. Quantum Filtering and Stabilization of Dissipative Quantum Systems via Augmented Neural Ordinary Differential Equations

    quant-ph 2025-09 conditional novelty 4.0 of 10

    An augmented neural ODE framework learns single-qubit states and time-dependent dissipation parameters from simulated weak-measurement data, and supports PD and LQR feedback control.

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