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
TorchSurv: A Lightweight Package for Deep Survival Analysis
Mélodie Monod, Peter Krusche, Qian Cao, Berkman Sahiner, Nicholas Petrick, David Ohlssen, Thibaud Coroller
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstruction
Sinisa Stekovic, Stefan Ainetter, Mattia D'Urso, Friedrich Fraundorfer, Vincent Lepetit