77 citations · 110 across the 23 of their papers we have counts for
5 papers · 1 filter
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
David M. Knigge, David R. Wessels, Riccardo Valperga +4
Recently, Conditional Neural Fields (NeFs) have emerged as a powerful modelling paradigm for PDEs, by learning solutions as flows in the latent space of the Conditional NeF. Althou…
Domain Adaptation with Cauchy-Schwarz Divergence
Wenzhe Yin, Shujian Yu, Yicong Lin +3
Domain adaptation aims to use training data from one or multiple source domains to learn a hypothesis that can be generalized to a different, but related, target domain. As such, h…
End-to-end Adaptive Dynamic Subsampling and Reconstruction for Cardiac MRI
George Yiasemis, Jan-Jakob Sonke, Jonas Teuwen
Accelerating dynamic MRI is vital for advancing clinical applications and improving patient comfort. Commonly, deep learning (DL) methods for accelerated dyn…
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation
Jie Liu, Wenzhe Yin, Haochen Wang +3
Few-shot point cloud segmentation seeks to generate per-point masks for previously unseen categories, using only a minimal set of annotated point clouds as reference. Existing prot…
Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT
Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen
Cone Beam CT (CBCT) is an essential imaging modality nowadays, but the image quality of CBCT still lags behind the high quality standards established by the conventional Computed T…