Author

P. Trahanias

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#machine learning Preprint Sep 2026

A Comparative Study of Counterfactual Explainers for Graph Neural Networks Enabling Multiple Types of Graph Edit

Counterfactual explanations for graph-structured data seek to determine minimal and realistic modifications required in an input graph to alter a model's prediction to a predefined output. Although counterfactual explainers that support modifying the graph by both adding and removing edges have recently emerged, there...

Maria Myrto Villia, Filippos Gouidis, T. Patkos et al. · 0 citations

Conference Jul 2026

Sim-to-Real Reinforcement Learning for Ball-Balancing Locomotion on Quadruped Robots

Non-prehensile manipulation of freely moving objects on a mobile base represents a significant challenge in underactuated robotics. This paper presents a sim-to-real reinforcement learning pipeline for a Unitree Go2 robot tasked with balancing a free-rolling ping-pong ball on a board mounted on its trunk while maintain...

Chang-Da Tian, Hamidreza Raei, Arash Ajoudani et al. · 2026 IEEE/ASME International... · 0 citations