Expressiveness and robustness of landscape features. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (GECCO (Companion), 2019)

Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy. - Quentin Renau; Carola Doerr; Johann Dréo; Benjamin Doerr (PPSN (2), 2020)

Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes. - Tome Eftimov; Gorjan Popovski; Quentin Renau; Peter Korosec; Carola Doerr (SSCI, 2020)

Experimental Data Set for the study "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy". - Quentin Renau; Carola Doerr; Johann Dréo; Benjamin Doerr (Zenodo, 2020)

Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (EvoApplications, 2021)

Exploratory Landscape Analysis Feature Values for the 24 Noiseless BBOB Functions. - Quentin Renau; Johann Dréo; Carola Doerr; Benjamin Doerr (Zenodo, 2021)

Automated algorithm selection for radar network configuration. - Quentin Renau; Johann Dréo; Alain Peres; Yann Semet; Carola Doerr; Benjamin Doerr (GECCO, 2022)

Landscape-Aware Selection of Metaheuristics for the Optimization of Radar Networks. (Sélection de Métaheuriques Guidée par le Paysage de Recherche pour l'Optimisation de Réseaux de Radars). - Quentin Renau (2022)

Towards optimisers that 'Keep Learning'. - Emma Hart; Ian Miguel; Christopher Stone 001; Quentin Renau (GECCO Companion, 2023)

On the Utility of Probing Trajectories for Algorithm-Selection. - Quentin Renau; Emma Hart (EvoApplications@EvoStar, 2024)

Ealain: A Camera Simulation Tool to Generate Instances for Multiple Classes of Optimisation Problem. - Quentin Renau; Johann Dréo; Emma Hart (GECCO Companion, 2024)

Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples. - Quentin Renau; Emma Hart (GECCO, 2024)

An Evaluation of Domain-Agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation. - Christopher Stone 001; Quentin Renau; Ian Miguel; Emma Hart (LION, 2024)

Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances. - Emma Hart; Quentin Renau; Kevin Sim; Mohamad Alissa (PPSN (2), 2024)

Identifying Easy Instances to Improve Efficiency of ML Pipelines for Algorithm-Selection. - Quentin Renau; Emma Hart (PPSN (2), 2024)

Improving Algorithm-Selection and Performance-Prediction via Learning Discriminating Training Samples. - Quentin Renau; Emma Hart (CoRR, 2024)

Improving Algorithm-Selectors and Performance-Predictors via Learning Discriminating Training Samples - Code and Data. - Quentin Renau; Emma Hart (Zenodo, 2024)

Evaluating the Robustness of Deep-learning Algorithm-selection Models by Evolving Adversarial Instances - Code and Data. - Quentin Renau; Emma Hart (Zenodo, 2024)

Identifying Easy Instances to Improve Efficiency of ML Pipelines for Algorithm-Selection - Code and Data. - Quentin Renau; Emma Hart (Zenodo, 2024)

Ealain: A Camera Simulation Tool to Generate Instances for Multiple Classes of Optimisation Problem. - Quentin Renau; Johann Dréo; Emma Hart (Zenodo, 2024)

Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing - Data. - Kevin Sim; Quentin Renau; Emma Hart (Zenodo, 2024)

Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model. - Quentin Renau; Emma Hart (EvoApplications (2), 2025)

Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing. - Kevin Sim; Quentin Renau; Emma Hart (EvoApplications (2), 2025)

Stalling in Space: Attractor Analysis for Any Algorithm. - Sarah L. Thomson; Quentin Renau; Diederick Vermetten; Emma Hart; Niki van Stein; Anna V. Kononova (EvoApplications (2), 2025)

Class Incremental Learning for Algorithm Selection. - Mate Botond Nemeth; Emma Hart; Kevin Sim; Quentin Renau (CoRR, 2025)