On the descriptive power of Neural-Networks as constrained Tensor Networks with exponentially large bond dimension
In many cases, Neural networks can be mapped into tensor networks with an exponentially large bond dimension. Here, we compare different sub-classes of neural network states, with their mapped tensor network counterpart for studying the ground state of short-range Hamiltonians. We show that when...
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| Format: | Article |
| Language: | English |
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SciPost
2021-02-01
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| Series: | SciPost Physics Core |
| Online Access: | https://scipost.org/SciPostPhysCore.4.1.001 |