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Lulu Cao

3 accepted papers

2025

Interpretable Solutions for Multi-Physics PDEs Using T-NNGP

AAAI 2025technical

Multiphysics simulation aims to predict and understand interactions between multiple physical phenomena, aiding in comprehending natural processes and guiding engineering design. The system of Partial Differential Equations (PDEs) is crucial for representing these physical fields, and solving these…

2024

An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations

AAAI 2024technical

In recent years, machine learning algorithms, especially deep learning, have shown promising prospects in solving Partial Differential Equations (PDEs). However, as the dimension increases, the relationship and interaction between variables become more complex, and existing methods are difficult to…

2023

Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs

AAAI 2023technical

Graph meta-learning has become a preferable paradigm for graph-based node classification with long-tail distribution, owing to its capability of capturing the intrinsic manifold of support and query nodes. Despite the remarkable success, graph meta-learning suffers from severe performance degradatio…

Cited by 13SourcePDFScholar