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20162024
most citedOPFData: Large-scale datasets for AC optimal power flow with topological perturbations

6 citations · 19 across the 5 of their papers we have counts for

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cs.LG2024★ 6 cited

OPFData: Large-scale datasets for AC optimal power flow with topological perturbations

Sean Lovett, Miha Zgubic, Sofia Liguori +6

Solving the AC optimal power flow problem (AC-OPF) is critical to the efficient and safe planning and operation of power grids. Small efficiency improvements in this domain have th…

cs.LG2024★ 4 cited

CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations

Luis Piloto, Sofia Liguori, Sephora Madjiheurem +6

Optimal Power Flow (OPF) refers to a wide range of related optimization problems with the goal of operating power systems efficiently and securely. In the simplest setting, OPF det…

cs.LG2020

Expected Eligibility Traces

Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel +3

The question of how to determine which states and actions are responsible for a certain outcome is known as the credit assignment problem and remains a central research question in…

cs.LG2019★ 4 cited

State2vec: Off-Policy Successor Features Approximators

Sephora Madjiheurem, Laura Toni

A major challenge in reinforcement learning (RL) is the design of agents that are able to generalize across tasks that share common dynamics. A viable solution is meta-reinforcemen…

cs.LG2019★ 5 cited

Representation Learning on Graphs: A Reinforcement Learning Application

Sephora Madjiheurem, Laura Toni

In this work, we study value function approximation in reinforcement learning (RL) problems with high dimensional state or action spaces via a generalized version of representation…