Nnodely - Neuralize Your Model
Gastone Pietro Rosati Papini, Alice Plebe, Mojtaba Sharifzadeh, Mattia Piazza, Sebastiano Taddei, Giovanni Scialla, Francesco Baroni, Davide De Martini
Abstract
Modeling and control of physical systems remain challenging for purely data-driven methods, which often lack interpretability and fail to leverage prior knowledge. Model-structured neural networks (MSNNs) embed physical laws into neural architectures; however, their design and implementation can be nontrivial. We present nnodely, an open-source framework that simplifies MSNN development through a modular workflow, improving interpretability, data efficiency, and deployment on resource-constrained platforms. The paper highlights the framework’s features, positions it within the landscape of existing tool, and demonstrates its effectiveness in two case studies. nnodely is released under the MIT license and is available at https://github.com/tonegas/nnodely