Hong-Jiong Tian

most citedA low-rank algorithm for solving Lyapunov operator

φ

-functions within the matrix-valued exponential integrators

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

math.PR2025

Explicit positivity preserving numerical method for linear stochastic volatility models driven by $α$ -stable process

Xiaotong Li, Wei Liu, Xuerong Mao +2

In this paper, we introduce a linear stochastic volatility model driven by $α$ -stable processes, which admits a unique positive solution. To preserve positivity, we modify the clas…

math.NA2025

Discovering Dynamics with Kolmogorov Arnold Networks: Linear Multistep Method-Based Algorithms and Error Estimation

Jintao Hu, Hongjiong Tian, Qian Guo

Uncovering the underlying dynamics from observed data is a critical task in various scientific fields. Recent advances have shown that combining deep learning techniques with linea…

math.NA2022★ 1 cited

A low-rank algorithm for solving Lyapunov operator $φ$ -functions within the matrix-valued exponential integrators

Dongping Li, Xiuying Zhang, Hongjiong Tian

In this work we present a low-rank algorithm for computing low-rank approximations of large-scale Lyapunov operator $φ$ -functions. These computations play a crucial role in impleme…

Explicit positivity preserving numerical method for linear stochastic volatility models driven by α-stable process

Discovering Dynamics with Kolmogorov Arnold Networks: Linear Multistep Method-Based Algorithms and Error Estimation

A low-rank algorithm for solving Lyapunov operator φ-functions within the matrix-valued exponential integrators

Explicit positivity preserving numerical method for linear stochastic volatility models driven by $α$ -stable process

A low-rank algorithm for solving Lyapunov operator $φ$ -functions within the matrix-valued exponential integrators