4 papers
Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis
Isabel Corona Guevara, Yeping Hu
Variance-based global sensitivity analysis (GSA) plays a key role in uncertainty quantification by identifying the contributions of uncertain inputs to the variability of the model…
Sparse Autoencoders as a Steering Basis for Phase Synchronization in Graph-Based CFD Surrogates
Yeping Hu, Ruben Glatt, Shusen Liu
Graph-based surrogate models provide fast alternatives to high-fidelity CFD solvers, but their opaque latent spaces and limited controllability restrict use in safety-critical sett…
M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations
Bo Lei, Victor M. Castillo, Yeping Hu
Mesh-based graph neural networks (GNNs) have become effective surrogates for PDE simulations, yet their deep message passing incurs high cost and over-smoothing on large, long-rang…
Interpreting CFD Surrogates through Sparse Autoencoders
Yeping Hu, Shusen Liu
Learning-based surrogate models have become a practical alternative to high-fidelity CFD solvers, but their latent representations remain opaque and hinder adoption in safety-criti…