Accuracy and capacity of Modern Hopfield networks with synaptic noise
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866916636388229120 |
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| author | Bhattacharjee, Sharba Martin, Ivar |
| author_facet | Bhattacharjee, Sharba Martin, Ivar |
| contents | We study the retrieval accuracy and capacity of modern Hopfield networks of with two-state (Ising) spins interacting via modified Hebbian $n$-spin interactions. In particular, we consider systems where the interactions deviate from the Hebb rule through additive or multiplicative noise or through clipping or deleting interactions. We find that the capacity scales as $N^{n-1}$ with the number of spins $N$ in all cases, but with a prefactor reduced compared to the Hebbian case. For $n=2$ our results agree with the previously known results for the conventional $n = 2$ Hopfield network. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_00241 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Accuracy and capacity of Modern Hopfield networks with synaptic noise Bhattacharjee, Sharba Martin, Ivar Disordered Systems and Neural Networks We study the retrieval accuracy and capacity of modern Hopfield networks of with two-state (Ising) spins interacting via modified Hebbian $n$-spin interactions. In particular, we consider systems where the interactions deviate from the Hebb rule through additive or multiplicative noise or through clipping or deleting interactions. We find that the capacity scales as $N^{n-1}$ with the number of spins $N$ in all cases, but with a prefactor reduced compared to the Hebbian case. For $n=2$ our results agree with the previously known results for the conventional $n = 2$ Hopfield network. |
| title | Accuracy and capacity of Modern Hopfield networks with synaptic noise |
| topic | Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2503.00241 |