Derives leading asymptotics for collision-time tails of integrable inhomogeneous Markov chains via steepest-descent analysis and Karlin-McGregor expansion, confirming a prediction for push-block particle systems.
Applications of Mathematics, vol
12 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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No local homogeneous rough path lift exists for γ-Hölder paths with γ≤1/2; for fBM with H>1/4 all local square-integrable lifts are stochastic translations of the canonical lift, with only the canonical satisfying extra invariances except at H=1/3.
Martingale Neural Operator uses Doob-Meyer factorization to output mean and low-rank covariance for stochastic PDE terminal laws, achieving large Wasserstein reductions versus diffusion baselines on tested SPDEs.
The paper proves existence and uniqueness of optimal controls for indefinite LQ problems in jump-diffusion systems with random coefficients by constructing a generalized stochastic Riccati equation with jumps from an algebraic inverse flow, under uniform convexity.
Generalized bridges with constraints solve Schrödinger problems, enabling broader financial equilibrium models with frictions and proving convergence of trading-cost equilibria to the classical Kyle model.
Defines resilience evaluation D^ρ π as the L1-limit of scaled dynamic risk measure applied to process increments, and derives its dual representation as worst-case conditional expectation of an effective drift when ρ arises from BSDEs with Lipschitz or quadratic drivers.
Characterizes duals of white-noise-driven continuous stochastic flows by explicit SDEs and introduces a self-dual polynomially self-repelling flow model.
MIOFlow 2.0 learns stochastic cellular trajectories from transcriptomics data via neural SDEs, unbalanced optimal transport for growth, and a joint latent space unifying gene expression with spatial features.
Constructs QMLE for drift parameter in singular Volterra SDE with small diffusion, proving path reconstruction error O(h^{1/2}) independent of roughness α and yielding efficient estimator as ε→0.
Causal PDE-Control Models combine causal drivers with PDE control and filtering to deliver interpretable dynamic portfolio rules that outperform benchmarks in Sharpe ratio and turnover on U.S. equity data.
Extends Gushchin's single-jump filtration framework to non-trivial initial sigma-algebra H and derives measurability, stopping-time, and martingale criteria via optional projections.
citing papers explorer
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Non-colliding space-time inhomogeneous Markov chains
Derives leading asymptotics for collision-time tails of integrable inhomogeneous Markov chains via steepest-descent analysis and Karlin-McGregor expansion, confirming a prediction for push-block particle systems.
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Locality of rough path lifts
No local homogeneous rough path lift exists for γ-Hölder paths with γ≤1/2; for fBM with H>1/4 all local square-integrable lifts are stochastic translations of the canonical lift, with only the canonical satisfying extra invariances except at H=1/3.
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Martingale Neural Operators: Learning Stochastic Marginals via Doob-Meyer Factorization
Martingale Neural Operator uses Doob-Meyer factorization to output mean and low-rank covariance for stochastic PDE terminal laws, achieving large Wasserstein reductions versus diffusion baselines on tested SPDEs.
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Indefinite Stochastic LQ Optimal Control for Jump-Diffusion Systems with Random Coefficients
The paper proves existence and uniqueness of optimal controls for indefinite LQ problems in jump-diffusion systems with random coefficients by constructing a generalized stochastic Riccati equation with jumps from an algebraic inverse flow, under uniform convexity.
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Schr\"odinger's problem with constraints
Generalized bridges with constraints solve Schrödinger problems, enabling broader financial equilibrium models with frictions and proving convergence of trading-cost equilibria to the classical Kyle model.
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Financial Resilience Evaluation: From Conditional Expectations to Dynamic Convex Risk Measures
Defines resilience evaluation D^ρ π as the L1-limit of scaled dynamic risk measure applied to process increments, and derives its dual representation as worst-case conditional expectation of an effective drift when ρ arises from BSDEs with Lipschitz or quadratic drivers.
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Continuous stochastic flows driven by white noise and their duals
Characterizes duals of white-noise-driven continuous stochastic flows by explicit SDEs and introduces a self-dual polynomially self-repelling flow model.
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MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data
MIOFlow 2.0 learns stochastic cellular trajectories from transcriptomics data via neural SDEs, unbalanced optimal transport for growth, and a joint latent space unifying gene expression with spatial features.
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Drift estimation for rough processes under small noise asymptotic : QMLE approach
Constructs QMLE for drift parameter in singular Volterra SDE with small diffusion, proving path reconstruction error O(h^{1/2}) independent of roughness α and yielding efficient estimator as ε→0.
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Causal PDE-Control Models for Dynamic Portfolio Optimization with Latent Drivers
Causal PDE-Control Models combine causal drivers with PDE control and filtering to deliver interpretable dynamic portfolio rules that outperform benchmarks in Sharpe ratio and turnover on U.S. equity data.
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Properties of a Special Type of Filtration and its Martingale Criteria
Extends Gushchin's single-jump filtration framework to non-trivial initial sigma-algebra H and derives measurability, stopping-time, and martingale criteria via optional projections.
- $L^{\alpha-1}$ distance between two one-dimensional stochastic differential equations with drift terms driven by a symmetric $\alpha$-stable process