AI RESEARCH
Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach
arXiv CS.LG
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ArXi:2602.18377v2 Announce Type: replace-cross Quantum reservoir computers (QRCs) have emerged as a promising approach to quantum machine learning, since they utilize the natural dynamics of quantum systems for data processing and are simple to train. Here, we consider $n$-qubit quantum extreme learning machines (QELMs) with initial-state encoding and continuous-time reservoir dynamics. QELMs are memoryless QRCs capable of various ML tasks, such as image classification and time series forecasting.