3 citations · 3 across the 1 of their papers we have counts for
24 papers
Cross-Sign Language Transfer Learning Using Domain Adaptation with Multi-scale Temporal Alignment
Keren Artiaga, Yang Li, Ercan Engin Kuruoglu +2
Sign language serves as a vital means of communication for individuals with hearing impairments, yet recognition resources for the over 100 distinct sign languages are severely lac…
Robust Learning on Heterogeneous Graphs with Heterophily: A Graph Structure Learning Approach
Yihan Zhang, Ercan E. Kuruoglu
Heterogeneous graphs with heterophily have emerged as a powerful abstraction for modeling complex real-world systems, where nodes of different types and labels interact in diverse…
Adaptive Spatio-temporal Estimation on the Graph Edges via Line Graph Transformation
Yi Yan, Ercan Engin Kuruoglu
Spatial-temporal estimation of signals on graph edges is challenging because most conventional Graph Signal Processing techniques are defined on the graph nodes. Leveraging the Lin…
Signal Processing over Time-Varying Graphs: A Systematic Review
Yi Yan, Jiacheng Hou, Zhenjie Song +1
As irregularly structured data representations, graphs have received a large amount of attention in recent years and have been widely applied to various real-world scenarios such a…
Function-Space Empirical Bayes Regularisation with Student's t Priors
Pengcheng Hao, Ercan Engin Kuruoglu
Bayesian deep learning (BDL) has emerged as a principled approach to produce reliable uncertainty estimates by integrating deep neural networks with Bayesian inference, and the sel…
Function-Space Empirical Bayes Regularisation with Large Vision-Language Model Priors
Pengcheng Hao, Huaze Tang, Ercan Engin Kuruoglu +1
Bayesian deep learning (BDL) provides a principled framework for reliable uncertainty quantification by combining deep neural networks with Bayesian inference. A central challenge…