Laure Crochepierre

According to our database1, Laure Crochepierre authored at least 11 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
A Semi-automatic Framework Towards Building Electricity Grid Infrastructure Management Ontology: A Case Study and Retrospective.
Proceedings of the Web Information Systems Engineering - WISE 2023, 2023

Grid2Onto: An Application Ontology for Knowledge Capitalisation to Assist Power Grid Operators.
Proceedings of the Joint Ontology Workshops 2023 Episode IX: The Quebec Summer of Ontology co-located with the 13th International Conference on Formal Ontology in Information Systems (FOIS 2023), 2023

2022
Apprentissage automatique interactif pour les opérateurs du réseau électrique. (Interactive Machine Learning for power system operators).
PhD thesis, 2022

A Reinforcement Learning Approach to Domain-Knowledge Inclusion Using Grammar Guided Symbolic Regression.
CoRR, 2022

Interactive Reinforcement Learning for Symbolic Regression from Multi-Format Human-Preference Feedbacks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Interactive Feature Extraction using Implicit Knowledge Elicitation : Application to Power System Expertise.
Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

Towards an AI Assistant for Power Grid Operators.
Proceedings of the HHAI 2022: Augmenting Human Intellect, 2022

2021
Approche interactive d'extraction de variables interprétables et explicatives pour la gestion des contraintes du réseau électrique français.
Proceedings of the Extraction et Gestion des Connaissances, 2021

2020
Towards an AI assistant for human grid operators.
CoRR, 2020

Interpretable Dimensionally-Consistent Feature Extraction from Electrical Network Sensors.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

2019
Interpreting Atypical Conditions in Systems with Deep Conditional Autoencoders: The Case of Electrical Consumption.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019


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