IEEE

Convolutional Variational Autoencoder for Anomaly Detection in On-Load Tap Changers

Abstract: Transformer outages significantly impact the reliability and cost efficiency of power systems. Studies indicate that approximately 30% of transformer failures stem from issues with on-load ...
Frontiers

RS-STGCN: Regional-Synergy Spatio-Temporal Graph Convolutional Network for emotion recognition

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...
IEEE

Conv4Rec: A 1-by-1 Convolutional Autoencoder for User Profiling Through Joint Analysis of Implicit and Explicit Feedback

Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...
GitHub

PyTorch Essential Training: Working with Images

This is the repository for the LinkedIn Learning course PyTorch Essential Training: Working with Images. The full course is available from LinkedIn Learning. Machine learning developers and data ...
GitHub

Variational autoencoder with Kolmogorov-Arnold Network for spatial domain detection.

Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121, torch_geometric==2.3.1, torch-sparse==0.6.18+pt21cu121, and torchvision==0.16.0+cu121. The stkan is an ...