"scientific machine learning" Papers
11 papers found
Conference
Collapsing Taylor Mode Automatic Differentiation
Felix Dangel, Tim Siebert, Marius Zeinhofer et al.
NEURIPS 2025arXiv:2505.13644
F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
Hangwei Zhang, Chun Kang, Yan Wang et al.
NEURIPS 2025arXiv:2509.23173
Physics-Informed Diffusion Models
Jan-Hendrik Bastek, WaiChing Sun, Dennis Kochmann
ICLR 2025arXiv:2403.14404
57
citations
PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling
Andrea Bonfanti, Ismael Medina, Roman List et al.
NEURIPS 2025arXiv:2510.21262
Semi-Implicit Neural Ordinary Differential Equations
Hong Zhang, Ying Liu, Romit Maulik
AAAI 2025paperarXiv:2412.11301
2
citations
UniFoil: A Universal Dataset of Airfoils in Transitional and Turbulent Regimes for Subsonic and Transonic Flows
Rohit Kanchi, Benjamin Melanson, Nithin Somasekharan et al.
NEURIPS 2025arXiv:2505.21124
2
citations
A Graph Dynamics Prior for Relational Inference
Liming Pan, Cheng Shi, Ivan Dokmanic
AAAI 2024paperarXiv:2306.06041
4
citations
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
Ning Liu, Yiming Fan, Xianyi Zeng et al.
ICML 2024spotlightarXiv:2312.11176
16
citations
Mechanistic Neural Networks for Scientific Machine Learning
Adeel Pervez, Francesco Locatello, Efstratios Gavves
ICML 2024arXiv:2402.13077
12
citations
Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller, Marius Zeinhofer
ICML 2024arXiv:2402.07318
19
citations
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
Yuyang Wang, Ahmed Elhag, Navdeep Jaitly et al.
ICML 2024arXiv:2311.17932
54
citations