Neural Architecture Evolution in Deep Reinforcement Learning for Continuous Control. - Jörg K. H. Franke; Gregor Köhler; Noor H. Awad; Frank Hutter (CoRR, 2019)

Hyperparameter Transfer Across Developer Adjustments. - Danny Stoll; Jörg K. H. Franke; Diane Wagner; Simon Selg; Frank Hutter (CoRR, 2020)

Sample-Efficient Automated Deep Reinforcement Learning. - Jörg K. H. Franke; Gregor Köhler; André Biedenkapp; Frank Hutter (ICLR, 2021)

Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design. - Jörg K. H. Franke; Frederic Runge; Frank Hutter (NeurIPS, 2022)

Why Do Machine Learning Practitioners Still Use Manual Tuning? A Qualitative Study. - Niklas Hasebrook; Felix Morsbach; Niclas Kannengießer; Jörg K. H. Franke; Frank Hutter; Ali Sunyaev (CoRR, 2022)

Towards Automated Design of Riboswitches. - Frederic Runge; Jörg K. H. Franke; Frank Hutter (CoRR, 2023)

Scalable Deep Learning for RNA Secondary Structure Prediction. - Jörg K. H. Franke; Frederic Runge; Frank Hutter (CoRR, 2023)

New Horizons in Parameter Regularization: A Constraint Approach. - Jörg K. H. Franke; Michael Hefenbrock; Gregor Köhler; Frank Hutter (CoRR, 2023)

Abstract: RecycleNet - Latent Feature Recycling Leads to Iterative Decision Refinement. - Gregor Köhler; Tassilo Wald; Constantin Ulrich; David Zimmerer; Paul F. Jaeger; Jörg K. H. Franke; Simon Kohl; Fabian Isensee; Klaus H. Maier-Hein (Bildverarbeitung für die Medizin, 2024)

Improving Deep Learning Optimization through Constrained Parameter Regularization. - Jörg K. H. Franke; Michael Hefenbrock; Gregor Köhler; Frank Hutter (NeurIPS, 2024)

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models. - Rhea Sukthanker; Arber Zela; Benedikt Staffler; Aaron Klein; Lennart Purucker; Jörg K. H. Franke; Frank Hutter (NeurIPS, 2024)

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement. - Gregor Köhler; Tassilo Wald; Constantin Ulrich; David Zimmerer; Paul F. Jaeger; Jörg K. H. Franke; Simon Kohl; Fabian Isensee; Klaus H. Maier-Hein (WACV, 2024)

Partial RNA design. - Frederic Runge; Jörg K. H. Franke; Daniel Fertmann; Rolf Backofen; Frank Hutter (Bioinform., 2024)

Rethinking Performance Measures of RNA Secondary Structure Problems. - Frederic Runge; Jörg K. H. Franke; Daniel Fertmann; Frank Hutter (CoRR, 2024)

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models. - Rhea Sanjay Sukthanker; Arber Zela; Benedikt Staffler; Jörg K. H. Franke; Frank Hutter (CoRR, 2024)

Fast Optimizer Benchmark. - Simon Blauth; Tobias Bürger; Zacharias Häringer; Jörg K. H. Franke; Frank Hutter (CoRR, 2024)

Transfer Learning for Finetuning Large Language Models. - Tobias Strangmann; Lennart Purucker; Jörg K. H. Franke; Ivo Rapant; Fabio Ferreira; Frank Hutter (CoRR, 2024)

Beyond Random Augmentations: Pretraining with Hard Views. - Fabio Ferreira; Ivo Rapant; Jörg K. H. Franke; Frank Hutter (ICLR, 2025)

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues. - Riccardo Grazzi; Julien Siems; Arber Zela; Jörg K. H. Franke; Frank Hutter; Massimiliano Pontil (ICLR, 2025)

KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks. - Dominik Scheuer; Frederic Runge; Jörg K. H. Franke; Michael T. Wolfinger; Christoph Flamm; Frank Hutter (ICLR, 2025)

Learning in Compact Spaces with Approximately Normalized Transformers. - Jörg K. H. Franke; Urs Spiegelhalter; Marianna Nezhurina; Jenia Jitsev; Frank Hutter; Michael Hefenbrock (CoRR, 2025)