Presentation by A. Lech at SPIE-ETAI, San Diego, 5 August 2025

DeepTrack2 Logo. (Image by J. Pineda)
Deeplay: Enhancing PyTorch with Customizable and Reusable Neural Networks
Alex Lech, Mirja Granfors, Benjamin Midtvedt, Jesús Pineda, Harshith Bachimanchi, Carlo Manzo, Giovanni Volpe
Date: 5 August 2025
Time: 12:00 – 12:15 PM
Place: Conv. Ctr. Room 4

Deeplay is a flexible Python library for deep learning that simplifies the definition and optimization of neural networks. It provides an intuitive framework that makes it easy to define and train models. With its modular design, deeplay lets users efficiently build and refine complex neural network architectures by seamlessly integrating reusable components based on PyTorch as well as adding a plethora of functionalities to alter and customize existing models without introducing boilerplate code. Deeplay is accompanied by a dedicated GitHub page, featuring extensive documentation, examples, and an active community for support and collaboration: https://github.com/DeepTrackAI/deeplay.

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