Selected work

Representative Papers

Non-Equilibrium Economics: A Physicist's Point of View

Jul 10, 2026

This study challenges the equilibrium paradigm of mainstream economics by investigating the endogenous origins of bubbles, crises, and inequality in economic systems. Drawing on complex systems theory, the authors develop a non-equilibrium dynamical “toy” model that integrates nonlinear dynamics and self-organized criticality to uncover three key mechanisms: path-dependent multiple equilibria, chaotic oscillations arising from dynamically inaccessible equilibria, and fragile stability induced by self-organized criticality. Remarkably, the model reproduces excessive volatility, endogenous crises, inflationary spirals, and persistent inequality—all without exogenous shocks—thereby offering a novel non-equilibrium explanation for macroeconomic instability and prompting a critical re-evaluation of conventional equilibrium-based frameworks.

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Covariance Shrinkage via Stochastic Interpolation

Jun 05, 2026

This work addresses the high statistical risk inherent in high-dimensional covariance estimation by reframing covariance shrinkage as a parameterized empirical risk minimization problem based on stochastic interpolation between source and target distributions. The proposed approach extends the theoretical foundations of classical shrinkage estimation through a synergistic integration of optimal transport couplings, eigenvector regularization induced by nonlinear flow maps, an early-stopping mechanism grounded in vector field regression, and an adaptive scheduling strategy. By unifying stochastic interpolation, neural estimators, and quadratic risk upper-bound analysis, the method demonstrates strong empirical performance on synthetic data and achieves superior regularization efficacy and estimation accuracy on real neuroimaging datasets.

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Recent publications

Latest Papers

Non-Equilibrium Economics: A Physicist's Point of View

Jul 10, 2026

This study challenges the equilibrium paradigm of mainstream economics by investigating the endogenous origins of bubbles, crises, and inequality in economic systems. Drawing on complex systems theory, the authors develop a non-equilibrium dynamical “toy” model that integrates nonlinear dynamics and self-organized criticality to uncover three key mechanisms: path-dependent multiple equilibria, chaotic oscillations arising from dynamically inaccessible equilibria, and fragile stability induced by self-organized criticality. Remarkably, the model reproduces excessive volatility, endogenous crises, inflationary spirals, and persistent inequality—all without exogenous shocks—thereby offering a novel non-equilibrium explanation for macroeconomic instability and prompting a critical re-evaluation of conventional equilibrium-based frameworks.

0 citationsRead paper

Covariance Shrinkage via Stochastic Interpolation

Jun 05, 2026

This work addresses the high statistical risk inherent in high-dimensional covariance estimation by reframing covariance shrinkage as a parameterized empirical risk minimization problem based on stochastic interpolation between source and target distributions. The proposed approach extends the theoretical foundations of classical shrinkage estimation through a synergistic integration of optimal transport couplings, eigenvector regularization induced by nonlinear flow maps, an early-stopping mechanism grounded in vector field regression, and an adaptive scheduling strategy. By unifying stochastic interpolation, neural estimators, and quadratic risk upper-bound analysis, the method demonstrates strong empirical performance on synthetic data and achieves superior regularization efficacy and estimation accuracy on real neuroimaging datasets.

0 citationsRead paper