4 papers
Data-Efficient Inference of Neural Fluid Fields via SciML Foundation Model
Yuqiu Liu, Jingxuan Xu, Mauricio Soroco +2
Recent developments in 3D vision have enabled significant progress in inferring neural fluid fields and realistic rendering of fluid dynamics. However, these methods require dense…
Learning Data-Efficient and Generalizable Neural Operators via Fundamental Physics Knowledge
Siying Ma, Mehrdad M. Zadeh, Mauricio Soroco +3
Recent advances in scientific machine learning (SciML) have enabled neural operators (NOs) to serve as powerful surrogates for modeling the dynamic evolution of physical systems go…
PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs
Mauricio Soroco, Jialin Song, Mengzhou Xia +3
While recent AI-for-math has made strides in pure mathematics, areas of applied mathematics, particularly PDEs, remain underexplored despite their significant real-world applicatio…
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining
Mishaal Kazmi, Hadrien Lautraite, Alireza Akbari +5
We present PANORAMIA, a privacy leakage measurement framework for machine learning models that relies on membership inference attacks using generated data as non-members. By relyin…