4 papers
Robust Basis Spline Decoupling for the Compression of Transformer Models
Joppe De Jonghe, Van Tien Pham, Mariya Ishteva
Decoupling is a powerful modeling paradigm for representing multivariate functions as compositions of linear transformations and univariate nonlinear functions. A single-layer deco…
Tensor-based Multi-layer Decoupling
Joppe De Jonghe, Konstantin Usevich, Philippe Dreesen +1
The decoupling of multivariate functions is a powerful modeling paradigm for learning multivariate input-output relations from data. For the single-layer case, established CPD-base…
Adaptive Subspace Modeling With Functional Tucker Decomposition
Noah Steidle, Joppe De Jonghe, Mariya Ishteva
Tensors provide a structured representation for multidimensional data, yet discretization can obscure important information when such data originates from continuous processes. We…
Non-parametric B-spline decoupling of multivariate functions
Joppe De Jonghe, Mariya Ishteva
Many scientific fields and applications require compact representations of multivariate functions. For this problem, decoupling methods are powerful techniques for representing the…