Squirrel: A Switching Hyperparameter Optimizer. - Noor H. Awad; Gresa Shala; Difan Deng; Neeratyoy Mallik; Matthias Feurer; Katharina Eggensperger; André Biedenkapp; Diederick Vermetten; Hao Wang 025; Carola Doerr; Marius Lindauer; Frank Hutter (CoRR, 2020)

Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization. - Julia Guerrero-Viu; Sven Hauns; Sergio Izquierdo; Guilherme Miotto; Simon Schrodi; Andre Biedenkapp; Thomas Elsken; Difan Deng; Marius Lindauer; Frank Hutter (CoRR, 2021)

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. - Marius Lindauer; Katharina Eggensperger; Matthias Feurer; André Biedenkapp; Difan Deng; Carolin Benjamins; René Sass; Frank Hutter (CoRR, 2021)

Searching in the Forest for Local Bayesian Optimization. - Difan Deng; Marius Lindauer (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

Efficient Automated Deep Learning for Time Series Forecasting. - Difan Deng; Florian Karl; Frank Hutter; Bernd Bischl; Marius Lindauer (ECML/PKDD (3), 2022)

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. - Marius Lindauer; Katharina Eggensperger; Matthias Feurer; André Biedenkapp; Difan Deng; Carolin Benjamins; Tim Ruhkopf; René Sass; Frank Hutter (J. Mach. Learn. Res., 2022)

MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information. - Tim Ruhkopf; Aditya Mohan; Difan Deng; Alexander Tornede; Frank Hutter; Marius Lindauer (Trans. Mach. Learn. Res., 2023)

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. - Bernd Bischl; Martin Binder; Michel Lang; Tobias Pielok; Jakob Richter; Stefan Coors; Janek Thomas; Theresa Ullmann; Marc Becker; Anne-Laure Boulesteix; Difan Deng; Marius Lindauer (WIREs Data. Mining. Knowl. Discov., 2023)

Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach. - Difan Deng; Marius Lindauer (CoRR, 2024)

Liebig's law of the minimum in the TGF-β/SMAD pathway. - Yuchao Li; Difan Deng; Chris Tina Höfer; Jihye Kim; Won Do Heo; Quanbin Xu; Xuedong Liu; Zhike Zi (PLoS Comput. Biol., 2024)

AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. - Alexander Tornede; Difan Deng; Theresa Eimer; Joseph Giovanelli; Aditya Mohan; Tim Ruhkopf; Sarah Segel; Daphne Theodorakopoulos; Tanja Tornede; Henning Wachsmuth; Marius Lindauer (Trans. Mach. Learn. Res., 2024)

Neural Attention Search. - Difan Deng; Marius Lindauer (CoRR, 2025)

carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks. - Carolin Benjamins; Helena Graf; Sarah Segel; Difan Deng; Tim Ruhkopf; Leona Hennig; Soham Basu; Neeratyoy Mallik; Edward Bergman; Deyao Chen; François Clément; Matthias Feurer; et al. (CoRR, 2025)