4 citations · 9 across the 26 of their papers we have counts for
10 papers · 1 filter
ParaFormer: A Generalized PageRank Graph Transformer for Graph Representation Learning
Chaohao Yuan, Zhenjie Song, Ercan Engin Kuruoglu +5
Graph Transformers (GTs) have emerged as a promising graph learning tool, leveraging their all-pair connected property to effectively capture global information. To address the ove…
SDG-L: A Semiparametric Deep Gaussian Process based Framework for Battery Capacity Prediction
Hanbing Liu, Yanru Wu, Yang Li +2
Lithium-ion batteries are becoming increasingly omnipresent in energy supply. However, the durability of energy storage using lithium-ion batteries is threatened by their dropping…
Monte Carlo Functional Regularisation for Continual Learning
Pengcheng Hao, Menghao Waiyan William Zhu, Ercan Engin Kuruoglu
Continual learning (CL) is crucial for the adaptation of neural network models to new environments. Although outperforming weight-space regularisation approaches, the functional re…
BrainNetMLP: An Efficient and Effective Baseline for Functional Brain Network Classification
Jiacheng Hou, Zhenjie Song, Ercan Engin Kuruoglu
Recent studies have made great progress in functional brain network classification by modeling the brain as a network of Regions of Interest (ROIs) and leveraging their connections…
ASD Classification on Dynamic Brain Connectome using Temporal Random Walk with Transformer-based Dynamic Network Embedding
Suchanuch Piriyasatit, Chaohao Yuan, Ercan Engin Kuruoglu
Autism Spectrum Disorder (ASD) is a complex neurological condition characterized by varied developmental impairments, especially in communication and social interaction. Accurate a…
Unifying Structural Proximity and Equivalence for Enhanced Dynamic Network Embedding
Suchanuch Piriyasatit, Chaohao Yuan, Ercan Engin Kuruoglu
Dynamic network embedding methods transform nodes in a dynamic network into low-dimensional vectors while preserving network characteristics, facilitating tasks such as node classi…