Abstract: Explainable artificial intelligence (XAI) approaches started to be studied in the last period to improve the interpretability of increasingly complex deep learning (DL) methods for remote ...

Replace the VAE algorithm in the paper《Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder》with the QBM-VAE algorithm, ...

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 ...

What if technology could bridge the gap between spoken language and sign language, empowering millions of people to communicate more seamlessly? With advancements in deep learning, this vision is no ...

This repository contains implementations of Convolutional KAN models with PyTorch Lightning training scripts for easy experimentation and training on various datasets including ImageNet and MNIST.

Classification of power system event data is a growing need, particularly where non-protective relaying-based sensors are used to monitor grid performance. Given the high burden of obtaining event ...