3 papers
cs.LG2026
T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation
Huy Truong, Alexander Lazovik, Victoria Degeler
Graph Neural Networks (GNNs) deployed in real-world systems typically have fixed weights, often leading to degraded performance under distribution shifts. This issue can be mitigat…
cs.LG2025
DiTEC-WDN: A Large-Scale Dataset of Hydraulic Scenarios across Multiple Water Distribution Networks
Huy Truong, Andrés Tello, Alexander Lazovik +1
Privacy restrictions hinder the sharing of real-world Water Distribution Network (WDN) models, limiting the application of emerging data-driven machine learning, which typically re…
cs.LG2024
Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks
Andres Tello, Huy Truong, Alexander Lazovik +1
Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide d…