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Learning to run a power network challenge for training topology controllers., , , , , , and . CoRR, (2019)Interpreting Atypical Conditions in Systems with Deep Conditional Autoencoders: The Case of Electrical Consumption., , , , , and . ECML/PKDD (3), volume 11908 of Lecture Notes in Computer Science, page 638-654. Springer, (2019)Guided Machine Learning for Power Grid Segmentation., , , and . ISGT Europe, page 1-6. IEEE, (2018)Composing aspects with aspects., and . AOSD, page 157-168. ACM, (2010)Composability of aspects., and . SPLAT@AOSD, page 5:1-5:6. ACM, (2008)Exploring grid topology reconfiguration using a simple deep reinforcement learning approach., , , , and . CoRR, (2020)Adversarial training for continuous robustness control problem in power systems., , and . CoRR, (2020)Creating StoryLines: Participatory Design with Power Grid Operators., , and . CHIRA (2), volume 1997 of Communications in Computer and Information Science, page 212-230. Springer, (2023)LEAP nets for power grid perturbations., , , , , , and . ESANN, (2019)Anticipating contingengies in power grids using fast neural net screening., , , , and . IJCNN, page 1-8. IEEE, (2018)