Nature

Kernel Methods in Adaptive Filtering and System Identification

Kernel methods have emerged as a powerful tool in adaptive filtering and system identification, enabling the processing and modelling of complex, nonlinear relationships in dynamic systems. By mapping ...
GitHub

diff of cos kernel for AMDGPU fails

Julia Version 1.12.2 Commit ca9b6662be4 (2025-11-20 16:25 UTC) Build Info: Official https://julialang.org release Platform Info: OS: Linux (x86_64-linux-gnu) CPU: 32 × AMD RYZEN AI MAX+ 395 w/ Radeon ...
IEEE

Deep Graph Wavelet Neural Networks Using Heat Kernel for Semi-supervised Node Classification

Abstract: Graph convolutional neural networks have demonstrated promising solutions for processing non-Euclidean data in tasks such as node classification. While existing graph convolution models aim ...
IEEE

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk

Abstract: This paper introduces novel nonparametric supervised learning techniques for classifying massive datasets, addressing key limitations of existing methods in Big and Streaming Data framework.
GitHub

kryptologyst/Graph-Generative-Models

A production-ready implementation of graph generative models using PyTorch Geometric. This project provides implementations of Variational Graph Autoencoders (VGAE), Graph Variational Autoencoders ...