Evolving look ahead controllers for energy optimal driving and path planning. - Adam Gaier; Alexander Asteroth (INISTA, 2014)

Evolution of optimal control for energy-efficient transport. - Adam Gaier; Alexander Asteroth (Intelligent Vehicles Symposium, 2014)

Evolutionary Design via Indirect Encoding of Non-Uniform Rational Basis Splines. - Adam Gaier (GECCO (Companion), 2015)

Data-efficient exploration, optimization, and modeling of diverse designs through surrogate-assisted illumination. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (GECCO, 2017)

Feature Space Modeling Through Surrogate Illumination. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (CoRR, 2017)

Multi-stage evolution of single- and multi-objective MCLP - Successive placement of charging stations. - Helge Spieker; Alexander Hagg; Adam Gaier; Stefanie Meilinger; Alexander Asteroth (Soft Comput., 2017)

Data-efficient neuroevolution with kernel-based surrogate models. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (GECCO, 2018)

Data-Efficient Design Exploration through Surrogate-Assisted Illumination. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (Evol. Comput., 2018)

Are quality diversity algorithms better at generating stepping stones than objective-based search? - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (GECCO (Companion), 2019)

Prediction of neural network performance by phenotypic modeling. - Alexander Hagg; Martin Zaefferer; Jörg Stork; Adam Gaier (GECCO (Companion), 2019)

Weight Agnostic Neural Networks. - Adam Gaier; David Ha (NeurIPS, 2019)

Discovering representations for black-box optimization. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (GECCO, 2020)

Automating Representation Discovery with MAP-Elites. - Adam Gaier; Alexander Asteroth; Jean-Baptiste Mouret (CoRR, 2020)

Accelerating Evolutionary Design Exploration with Predictive and Generative Models. (Accélérer l'exploration de la conception par algorithme évolutionniste grâce à des modèles prédictifs et génératifs). - Adam Gaier (2020)

COIL: Constrained optimization in learned latent space: learning representations for valid solutions. - Peter J. Bentley; Soo Ling Lim; Adam Gaier; Linh Tran (GECCO Companion, 2022)

A discretization-free metric for assessing quality diversity algorithms. - Paul Kent; Jürgen Branke; Adam Gaier; Jean-Baptiste Mouret (GECCO Companion, 2022)

Evolving Through the Looking Glass: Learning Improved Search Spaces with Variational Autoencoders. - Peter J. Bentley; Soo Ling Lim; Adam Gaier; Linh Tran (PPSN (1), 2022)

T-DominO - Exploring Multiple Criteria with Quality-Diversity and the Tournament Dominance Objective. - Adam Gaier; James Stoddart; Lorenzo Villaggi; Peter J. Bentley (PPSN (2), 2022)

Editorial to the "Evolutionary Reinforcement Learning" Special Issue. - Adam Gaier; Giuseppe Paolo; Antoine Cully (ACM Trans. Evol. Learn. Optim., 2023)

PlotMap: Automated Layout Design for Building Game Worlds. - Yi Wang; Jieliang Luo; Adam Gaier; Evan Atherton; Hilmar Koch (CoG, 2024)

Generative Design through Quality-Diversity Data Synthesis and Language Models. - Adam Gaier; James Stoddart; Lorenzo Villaggi; Shyam Sudhakaran (GECCO, 2024)

Language Model Crossover: Variation through Few-Shot Prompting. - Elliot Meyerson; Mark J. Nelson; Herbie Bradley; Adam Gaier; Arash Moradi Karkaj; Amy K. Hoover; Joel Lehman (ACM Trans. Evol. Learn. Optim., 2024)

Bayesian Optimization for Quality Diversity Search With Coupled Descriptor Functions. - Paul Kent; Adam Gaier; Jean-Baptiste Mouret; Juergen Branke (IEEE Trans. Evol. Comput., 2025)

Full Domain Analysis in Fluid Dynamics. - Alexander Hagg; Adam Gaier; Dominik Wilde; Alexander Asteroth; Holger Foysi; Dirk Reith (CoRR, 2025)