Difan Deng

According to our database, Difan Deng authored at least 14 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2026

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models.

Difan Deng, Andreas Bentzen Winje, Lukas Fehring, Marius Lindauer

CoRR, February, 2026

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, Katharina Eggensperger, Frank Hutter, Carola Doerr, Marius Lindauer

CoRR, June, 2025

Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach.

Difan Deng, Marius Lindauer

Trans. Mach. Learn. Res., 2025

Neural Attention Search.

Difan Deng, Marius Lindauer

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

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

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

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

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

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

Efficient Automated Deep Learning for Time Series Forecasting.

Difan Deng, Florian Karl, Frank Hutter, Bernd Bischl, Marius Lindauer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Searching in the Forest for Local Bayesian Optimization.

Difan Deng, Marius Lindauer

Proceedings of the ECML/PKDD Workshop on Meta-Knowledge Transfer, 2022

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

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

2020

Squirrel: A Switching Hyperparameter Optimizer.

Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter

CoRR, 2020