We consider the problem of discretization of neural operators between Hilbert spaces in a general framework including skip connections. We focus on bijec-tive neural operators through the lens of diffeomorphisms in infinite dimensions.

Project lead, main contributor, correspondence to alexandre.rame@isir.upmc.fr. Equal experimental contribution, order determined at random. Further information and resources related to this project can be found on this website.

Left: The reward function is a mixture of Gaussian, and the offline data distribution is unbalanced with most samples located in low-reward states.

Proceedings of the International Conference on Machine Learning 2024