Poster "scientific machine learning" Papers

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Collapsing Taylor Mode Automatic Differentiation

Felix Dangel, Tim Siebert, Marius Zeinhofer et al.

NeurIPS 2025posterarXiv:2505.13644

F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning

Hangwei Zhang, Chun Kang, Yan Wang et al.

NeurIPS 2025posterarXiv:2509.23173

Physics-Informed Diffusion Models

Jan-Hendrik Bastek, WaiChing Sun, Dennis Kochmann

ICLR 2025posterarXiv:2403.14404
52
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 2025posterarXiv:2505.21124

Mechanistic Neural Networks for Scientific Machine Learning

Adeel Pervez, Francesco Locatello, Efstratios Gavves

ICML 2024poster

Position: Optimization in SciML Should Employ the Function Space Geometry

Johannes Müller, Marius Zeinhofer

ICML 2024poster

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation

Yuyang Wang, Ahmed Elhag, Navdeep Jaitly et al.

ICML 2024poster