QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
quant-ph 2verdicts
UNVERDICTED 2representative citing papers
Formation of a bound state in the agent-noise energy spectrum restores QRL performance to the noiseless case for eigenstate solving under non-Markovian decoherence.
citing papers explorer
-
QKAN: quantum Kolmogorov-Arnold networks with applications in machine learning and multivariate state preparation
QKAN is a quantum algorithmic framework using block-encodings and QSVT to implement wide-and-shallow networks for quantum learning and compositional state preparation.
-
Noise-Resilient Quantum Reinforcement Learning
Formation of a bound state in the agent-noise energy spectrum restores QRL performance to the noiseless case for eigenstate solving under non-Markovian decoherence.