Qijing Shen

According to our database, Qijing Shen authored at least 8 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

A new local time-decoupled squared Wasserstein-2 method for training stochastic neural networks to reconstruct uncertain parameters in dynamical systems.

Mingtao Xia, Qijing Shen, Philip K. Maini, Eamonn A. Gaffney, Alex Mogilner

Neural Networks, 2026

2025

Squared Wasserstein-2 loss functions for efficient learning of stochastic differential equations.

Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou

Mach. Learn., November, 2025

A generalized Wasserstein-2 distance approach for efficient reconstruction of random field models using stochastic neural networks.

Mingtao Xia, Qijing Shen

CoRR, July, 2025

2024

Learning unbounded-domain spatiotemporal differential equations using adaptive spectral methods.

Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou

J. Appl. Math. Comput., October, 2024

A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty.

Mingtao Xia, Qijing Shen

CoRR, 2024

An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks.

Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou

CoRR, 2024

Squared Wasserstein-2 Distance for Efficient Reconstruction of Stochastic Differential Equations.

Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou

CoRR, 2024

2023

A Spectral Approach for Learning Spatiotemporal Neural Differential Equations.

Mingtao Xia, Xiangting Li, Qijing Shen, Tom Chou

CoRR, 2023