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Error Analysis of Tensor-Train Cross Approximation
Tensor train decomposition is widely used in machine learning and quantum physics due to its concise representation of high-dimensional tensors, overcoming the curse of dimensionality.
Unsupervised machine learning of quantum phase transitions using diffusion maps
Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is available.
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