Adam Paszke
Publications by Year
Research Areas
Parallel Computing and Optimization Techniques, Logic, programming, and type systems, Advanced Neural Network Applications, Formal Methods in Verification, Embedded Systems Design Techniques
Most-Cited Works
- → PyTorch: An Imperative Style, High-Performance Deep Learning Library(2019)16,163 cited
- Automatic differentiation in PyTorch(2017)
- → ENet: A Deep Neural Network Architecture for Real-Time Semantic\n Segmentation(2016)1,258 cited
- → An Analysis of Deep Neural Network Models for Practical Applications(2016)981 cited
- → PyTorch distributed(2020)413 cited
- → PyTorch Distributed: Experiences on Accelerating Data Parallel Training(2020)116 cited
- → Evaluation of neural network architectures for embedded systems(2017)45 cited
- → Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching(2021)14 cited
- → You Only Linearize Once: Tangents Transpose to Gradients(2023)13 cited