Johannes Wehrstein

According to our database, Johannes Wehrstein authored at least 6 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Opening The Black-Box: Explaining Learned Cost Models For Databases.

Roman Heinrich, Oleksandr Havrylov, Manisha Luthra, Johannes Wehrstein, Carsten Binnig

CoRR, July, 2025

JOB-Complex: A Challenging Benchmark for Traditional & Learned Query Optimization.

Johannes Wehrstein, Timo Eckmann, Roman Heinrich, Carsten Binnig

CoRR, July, 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, June, 2025

GRACEFUL: A Learned Cost Estimator For UDFs.

Johannes Wehrstein, Tiemo Bang, Roman Heinrich, Carsten Binnig

CoRR, March, 2025

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

2021

Noise-Resilient Empirical Performance Modeling with Deep Neural Networks.

Marcus Ritter, Alexander Geiß, Johannes Wehrstein, Alexandru Calotoiu, Thorsten Reimann, Torsten Hoefler, Felix Wolf

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021