Noise-Resilient Empirical Performance Modeling with Deep Neural Networks. - Marcus Ritter; Alexander Geiß; Johannes Wehrstein; Alexandru Calotoiu; Thorsten Reimann; Torsten Hoefler; Felix Wolf 001 (IPDPS, 2021)

LLMs and Databases: A Synergistic Approach to Data Utilization. - Fatma Ozcan; Yeounoh Chung; Yannis Chronis; Yu Gan; Yawen Wang; Carsten Binnig; Johannes Wehrstein; Gaurav Tarlok Kakkar; Sami Abu-el-haija (IEEE Data Eng. Bull., 2025)

GRACEFUL: A Learned Cost Estimator For UDFs. - Johannes Wehrstein; Tiemo Bang; Roman Heinrich; Carsten Binnig (CoRR, 2025)

How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks. - Roman Heinrich; Manisha Luthra; Johannes Wehrstein; Harald Kornmayer; Carsten Binnig (Proc. ACM Manag. Data, 2025)

JOB-Complex: A Challenging Benchmark for Traditional & Learned Query Optimization. - Johannes Wehrstein; Timo Eckmann; Roman Heinrich; Carsten Binnig (CoRR, 2025)

Opening The Black-Box: Explaining Learned Cost Models For Databases. - Roman Heinrich; Oleksandr Havrylov; Manisha Luthra; Johannes Wehrstein; Carsten Binnig (CoRR, 2025)