IEEE

Modified Overcomplete Autoencoder for Anomaly Detection Based on TinyML

Abstract: This letter explores the architecture of tiny machine learning (TinyML). Deploying machine learning into embedded devices is challenging due to the limited computation power and memory space ...
IEEE

Target-Embedding Autoencoder With Knowledge Distillation for Multi-Label Classification

Abstract: In the task of multi-label classification, it is a key challenge to determine the correlation between labels. One solution to this is the Target Embedding Autoencoder (TEA), but most ...
GitHub

An Efficient Implementation of Kolmogorov-Arnold Network

This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The problem is in the sparsification which is claimed to ...
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 ...