Alex Lech, Mirja Granfors, Jiacheng Huang, Benjamin Midtvedt, Jesús Pineda, Harshith Bachimanchi, Carlo Manzo, Giovanni Volpe
Date: 23 August 2026
Time: 2:15 PM – 2:30 PM PDT
Place: Conv. Ctr. Room 2
Deeplay is a Python-based deep learning library that extends PyTorch, addressing limitations in modularity and reusability commonly encountered in neural network development. Built with a core philosophy of modularity and adaptability. Unlike traditional PyTorch modules, Deeplay allows the properties of submodules to be modified after creation. Layers, blocks, or activation functions can be replaced or reconfigured without rewriting the surrounding architecture, which reduces boilerplate code, improves reuse, and simplifies ablation studies.