Oct 11, 2023 · In this paper, we study PHNNs convergence and propose parameterized hypercomplex identity initialization (PHYDI), a method to improve their convergence at ...
In this paper, we study PHNNs convergence and propose parameterized hypercomplex identity initialization (PHYDI), a method to improve their convergence at ...
Oct 11, 2023 · PHYDI: INITIALIZING PARAMETERIZED HYPERCOMPLEX NEURAL NETWORKS AS. IDENTITY FUNCTIONS. Matteo Mancanelli, Eleonora Grassucci, Aurelio Uncini ...
In this paper, we study PHNNs convergence and propose parameterized hypercomplex identity initialization (PHYDI), a method to improve their convergence at ...
PHYDI. Public. Official PyTorch repository of "PHYDI: Initializing Parameterized Hypercomplex Neural Networks as Identity Functions". Python. • 1• 3• 0• 0 ...
Co-authors ; Phydi: Initializing Parameterized Hypercomplex Neural Networks As Identity Functions. M Mancanelli, E Grassucci, A Uncini, D Comminiello. 2023 IEEE ...
6 days ago · Phydi: Initializing Parameterized Hypercomplex Neural Networks As Identity Functions. Conference Paper. Sep 2023. Matteo ...
In this paper, we define the parameterization of hypercomplex convolutional layers and introduce the family of parameterized hypercomplex neural networks (PHNNs) ...
In this paper, we study PHNNs convergence and propose parameterized hypercomplex identity initialization (PHYDI), a method to improve their convergence at ...
PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex ...
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This article defines the parameterization of hypercomplex convolutional layers and introduces the family of parameterized hypercomplex neural networks ...