GitHub

Compiled torch model has much worse performance than non-compiled version.

type:supportUser is asking for help / asking an implementation question. Stackoverflow would be better suited.User is asking for help / asking an implementation question. Stackoverflow would be better ...
Scientific Research Publishing

Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J. et al. (2019). PyTorch: An Imperative Style, High-Performance Deep Learning Library. Advances in Neural Information ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...
IEEE

Biasing Federated Learning With a New Adversarial Graph Attention Network

Abstract: Fairness in Federated Learning (FL) is imperative not only for the ethical utilization of technology but also for ensuring that models provide accurate, equitable, and beneficial outcomes ...
marktechpost

Hierarchical Graph Masked AutoEncoders (Hi-GMAE): A Novel Multi-Scale GMAE Framework Designed to Handle the Hierarchical Structures within Graph

In graph analysis, the need for labeled data presents a significant hurdle for traditional supervised learning methods, particularly within academic, social, and biological networks. To overcome this ...
IEEE

Glaucus: A Complex-Valued Radio Signal Autoencoder

Abstract: A complex-valued autoencoder neural network ca-pable of compressing & denoising radio frequency signals with arbitrary model scaling is proposed. Complex-valued time sam-ples received with ...
GitHub

Variational Autoencoder in tensorflow and pytorch

Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...