প্রচ্ছদ

A Library for Learning Neural Operators

সংরক্ষণ করুন:
প্রকাশিত:arXiv.org (Dec 17, 2024), p. n/a
প্রধান লেখক: Kossaifi, Jean
অন্যান্য লেখক: Kovachki, Nikola, Li, Zongyi, Pitt, David, Liu-Schiaffini, Miguel, George, Robert Joseph, Bonev, Boris, Azizzadenesheli, Kamyar, Berner, Julius, Anandkumar, Anima
প্রকাশিত:
Cornell University Library, arXiv.org
বিষয়গুলি:
Learning curves
Python
Function space
Convergence
Neural networks
Operators (mathematics)
Discretization
Open source software
Euclidean geometry
অনলাইন ব্যবহার করুন:Citation/Abstract
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সার সংক্ষেপ:We present NeuralOperator, an open-source Python library for operator learning. Neural operators generalize neural networks to maps between function spaces instead of finite-dimensional Euclidean spaces. They can be trained and inferenced on input and output functions given at various discretizations, satisfying a discretization convergence properties. Built on top of PyTorch, NeuralOperator provides all the tools for training and deploying neural operator models, as well as developing new ones, in a high-quality, tested, open-source package. It combines cutting-edge models and customizability with a gentle learning curve and simple user interface for newcomers.
আইএসএসএন:2331-8422
সম্পদ:Engineering Database