Identifiable Feature Learning for Spatial Data with Nonlinear ICA

Hermanni Hälvä, Jonathan So, Richard E. Turner +1

Recently, nonlinear ICA has surfaced as a popular alternative to the many heuristic models used in deep representation learning and disentanglement. An advantage of nonlinear ICA i…