Holographic isoTNS represent volume-law entangled states including arbitrary fermionic Gaussian states, Clifford states, and certain short-time evolved states using an extra network dimension with isometric constraints.
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A two-layer tensor-augmented CNN reaches 93.7% test accuracy on Fashion-MNIST, matching or exceeding deeper models like VGG-16 and GoogLeNet by using tensors for richer expressivity.
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Holographic Representation of One-Dimensional Many-Body Quantum States via Isometric Tensor Networks
Holographic isoTNS represent volume-law entangled states including arbitrary fermionic Gaussian states, Clifford states, and certain short-time evolved states using an extra network dimension with isometric constraints.
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Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels
A two-layer tensor-augmented CNN reaches 93.7% test accuracy on Fashion-MNIST, matching or exceeding deeper models like VGG-16 and GoogLeNet by using tensors for richer expressivity.