arXiv stat.ML
· Papers
Kernel Methods for Learning Operators with Multiple Inputs and Outputs
arXiv:2608.11831v1 Announce Type: cross Abstract: Learning mappings between infinite-dimensional objects is a central challenge in scientific machine learning. We introduce a general kernel-based encoder-decoder framework for operator learning that separates observation, representation, learning, and reconstruction. We