Pytorch Model
PyTorch is a widely used open-source machine learning framework primarily focused on facilitating the development and deployment of deep learning models. Current research emphasizes improving efficiency and accessibility through optimized implementations of various algorithms (e.g., symbolic regression, bundle adjustment, spiking neural networks) and the creation of specialized toolkits for tasks like species distribution modeling, adversarial machine learning, and multi-objective optimization. This framework's impact stems from its ease of use, extensibility, and support for GPU acceleration, enabling researchers and practitioners across diverse scientific disciplines to leverage deep learning for complex problems.
Papers
TorchSISSO: A PyTorch-Based Implementation of the Sure Independence Screening and Sparsifying Operator for Efficient and Interpretable Model Discovery
Madhav Muthyala, Farshud Sorourifar, Joel A. Paulson
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications
Pohsun Feng, Ziqian Bi, Yizhu Wen, Xuanhe Pan, Benji Peng, Ming Liu, Jiawei Xu, Keyu Chen, Junyu Liu, Caitlyn Heqi Yin, Sen Zhang, Jinlang Wang, Qian Niu, Ming Li, Tianyang Wang