6 papers
Storage capacity of perceptron with variable selection
Yingying Xu, Masayuki Ohzeki, Yoshiyuki Kabashima
A central challenge in machine learning is to distinguish genuine structure from chance correlations in high-dimensional data. In this work, we address this issue for the perceptro…
Quantum effects in rotationally invariant spin glass models
Yoshinori Hara, Yoshiyuki Kabashima
This study investigates the quantum effects in transverse-field Ising spin glass models with rotationally invariant random interactions. The primary aim is to evaluate the validity…
Improving Decoupled Posterior Sampling for Inverse Problems using Data Consistency Constraint
Zhi Qi, Shihong Yuan, Yulin Yuan +3
Diffusion models have shown strong performances in solving inverse problems through posterior sampling while they suffer from errors during earlier steps. To mitigate this issue, s…
Alpha helices are more evolutionarily robust to environmental perturbations than beta sheets: Bayesian learning and statistical mechanics for protein evolution
Tomoei Takahashi, George Chikenji, Kei Tokita +1
How typical elements that shape organisms, such as protein secondary structures, have evolved, or how evolutionarily susceptible/resistant they are to environmental changes, are si…
Exact Replica Symmetric solution for transverse field Hopfield model under finite Trotter size
Koki Okajima, Yoshiyuki Kabashima
We analyze the quantum Hopfield model in which an extensive number of patterns are embedded in the presence of a uniform transverse field. This analysis employs the replica method…
Forecasting long-time dynamics in quantum many-body systems by dynamic mode decomposition
Ryui Kaneko, Masatoshi Imada, Yoshiyuki Kabashima +1
Reliable numerical computation of quantum dynamics is a fundamental challenge when the long-ranged quantum entanglement plays essential roles as in the cases governed by quantum cr…