activity
20222025
most citedA Causality-Based Learning Approach for Discovering the Underlying Dynamics of Complex Systems from Partial Observations with Stochastic Parameterization

15 citations · 42 across the 8 of their papers we have counts for

collaborators

9 papers

stat.AP2025

A Physics-Informed Variational Inference Framework for Identifying Attributions of Extreme Stress Events in Low-Grain Polycrystals

Yinling Zhang, Samuel D. Dunham, Curt A. Bronkhorst +1

Polycrystalline metal failure often begins with stress concentration at grain boundaries. Identifying which microstructural features trigger these events is important but challengi…

cs.CV2025

Adaptive Confidence-Wise Loss for Improved Lens Structure Segmentation in AS-OCT

Zunjie Xiao, Xiao Wu, Tianhang Liu +5

Precise lens structure segmentation is essential for the design of intraocular lenses (IOLs) in cataract surgery. Existing deep segmentation networks typically weight all pixels eq…

physics.ao-ph2025

A Simple Intermediate Coupled MJO-ENSO Model: Multiscale Interactions and ENSO Complexity

Yinling Zhang, Nan Chen, Charlotte Moser

The Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) are two dominant modes of tropical climate variability, each with profound global weather impacts. W…

physics.ao-ph2024

A Stochastic Conceptual Model for the Coupled ENSO and MJO

Yinling Zhang, Charlotte Moser, Nan Chen

Understanding the interactions between the El Nino-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO) is essential to studying climate variabilities and predicting…

cs.LG2024★ 10 cited

CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation

Chuanqi Chen, Nan Chen, Yinling Zhang +1

Deep learning is widely used to predict complex dynamical systems in many scientific and engineering areas. However, the black-box nature of these deep learning models presents sig…

math.DS2024

A Physics-Informed Auto-Learning Framework for Developing Stochastic Conceptual Models for ENSO Diversity

Yinling Zhang, Nan Chen, Jerome Vialard +1

Understanding ENSO dynamics has tremendously improved over the past decades. However, one aspect still poorly understood or represented in conceptual models is the ENSO diversity i…

cond-mat.mtrl-sci2023★ 12 cited

Data-Driven Statistical Reduced-Order Modeling and Quantification of Polycrystal Mechanics Leading to Porosity-Based Ductile Damage

Yinling Zhang, Nan Chen, Curt A. Bronkhorst +2

Predicting the process of porosity-based ductile damage in polycrystalline metallic materials is an essential practical topic. Ductile damage and its precursors are represented by…

physics.geo-ph2022★ 5 cited

Rigorous Derivation of Stochastic Conceptual Models for the El Niño-Southern Oscillation from a Spatially-Extended Dynamical System

Nan Chen, Yinling Zhang

El Niño-Southern Oscillation (ENSO) is the most predominant interannual variability in the tropics, significantly impacting global weather and climate. In this paper, a framework o…

math.DS2022★ 15 cited

A Causality-Based Learning Approach for Discovering the Underlying Dynamics of Complex Systems from Partial Observations with Stochastic Parameterization

Nan Chen, Yinling Zhang

Discovering the underlying dynamics of complex systems from data is an important practical topic. Constrained optimization algorithms are widely utilized and lead to many successes…