18 citations · 34 across the 7 of their papers we have counts for
4 papers · 1 filter
Can Large Language Models Reason and Optimize Under Constraints?
Fabien Bernier, Salah Ghamizi, Pantelis Dogoulis +1
Large Language Models (LLMs) have demonstrated great capabilities across diverse natural language tasks; yet their ability to solve abstraction and optimization problems with const…
KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
Pantelis Dogoulis, Karim Tit, Maxime Cordy
In the modern context of power systems, rapid, scalable, and physically plausible power flow predictions are essential for ensuring the grid's safe and efficient operation. While t…
Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories
Pantelis Dogoulis, Fabien Bernier, Félix Fourreau +2
Many real-world machine learning tasks require outputs that satisfy hard constraints, such as physical conservation laws, structured dependencies in graphs, or column-level relatio…
Robustness Analysis of AI Models in Critical Energy Systems
Pantelis Dogoulis, Matthieu Jimenez, Salah Ghamizi +2
This paper analyzes the robustness of state-of-the-art AI-based models for power grid operations under the security criterion. While these models perform well in regular grid…