WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …

Presently, neural networks are widely employed to accurately estimate 2D displacements
and associated uncertainties from Inertial Measurement Unit (IMU) data that can be …

Deep neural networks (DNNs) in 3D scenes show a strong capability of extracting high-level
semantic features and significantly promote research in the 3D field. 3D shapes and scenes …

The quest for robust and generalizable machine learning models has driven recent interest
in exploiting symmetries through equivariant neural networks. In the context of PDE solvers …

One of the guiding principles for designing AI-based weather forecasting systems is to
embed physical constraints as inductive priors in the neural network architecture. A popular …

The advents of Artificial Intelligence (AI)-driven models marks a paradigm shift in risk
management strategies for meteorological hazards. This study specifically employs tropical …

Traditional convolutional neural networks (CNNs) face significant challenges when applied
to omnidirectional images due to the non-uniform sampling inherent in equirectangular …