3 papers
cs.LG2026
Derived Fields Increase the Recoverable Information in Budgeted Neural PDE Surrogate
Wenshuo Wang, Fan Zhang
For neural surrogates of time-dependent partial differential equations (PDEs), storage and memory budgets require training data to be obtained by coarsening and quantizing very-hig…
gr-qc2024
Efficient Gravitational Wave Parameter Estimation via Knowledge Distillation: A ResNet1D-IAF Approach
Xihua Zhu, Yiqian Yang, Fan Zhang
With the rapid development of gravitational wave astronomy, the increasing number of detected events necessitates efficient methods for parameter estimation and model updates. This…
cs.LG2024
Adaptive Epsilon Adversarial Training for Robust Gravitational Wave Parameter Estimation Using Normalizing Flows
Yiqian Yang, Xihua Zhu, Fan Zhang
Adversarial training with Normalizing Flow (NF) models is an emerging research area aimed at improving model robustness through adversarial samples. In this study, we focus on appl…