53 citations · 170 across the 22 of their papers we have counts for
5 papers · 1 filter
Data-driven solar forecasting enables near-optimal economic decisions
Zhixiang Dai, Minghao Yin, Xuanhong Chen +27
Solar energy adoption is critical to achieving net-zero emissions. However, it remains difficult for many industrial and commercial actors to decide on whether they should adopt di…
Physics-Aware Neural Operators for Direct Inversion in 3D Photoacoustic Tomography
Jiayun Wang, Yousuf Aborahama, Arya Khokhar +10
Learning physics-constrained inverse operators-rather than post-processing physics-based reconstructions-is a broadly applicable strategy for problems with expensive forward models…
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale
Boris Bonev, Thorsten Kurth, Ankur Mahesh +7
FourCastNet 3 advances global weather modeling by implementing a scalable, geometric machine learning (ML) approach to probabilistic ensemble forecasting. The approach is designed…
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
Julius Berner, Miguel Liu-Schiaffini, Jean Kossaifi +4
A wide range of scientific problems, such as those described by continuous-time dynamical systems and partial differential equations (PDEs), are naturally formulated on function sp…
Attention on the Sphere
Boris Bonev, Max Rietmann, Andrea Paris +2
We introduce a generalized attention mechanism for spherical domains, enabling Transformer architectures to natively process data defined on the two-dimensional sphere - a critical…