PyTorch: An Imperative Style, High-Performance Deep Learning Library. - Adam Paszke; Sam Gross; Francisco Massa; Adam Lerer; James Bradbury; Gregory Chanan; Trevor Killeen; Zeming Lin; Natalia Gimelshein; Luca Antiga; Alban Desmaison; Andreas Köpf; et al. (NeurIPS, 2019)

PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. - Shen Li; Pritam Damania; Luca Wehrstedt; Rohan Varma; Omkar Salpekar; Pavel Belevich; Howard Huang; Yanli Zhao; Lucas Hosseini; Wanchao Liang; Hongyi Jia; Shihao Xu; et al. (MLSys, 2023)

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. - Jason Ansel; Edward Z. Yang; Horace He; Natalia Gimelshein; Animesh Jain; Michael Voznesensky; Bin Bao; Peter Bell 008; David Berard; Evgeni Burovski; Geeta Chauhan; Anjali Chourdia; et al. (ASPLOS (2), 2024)