4 citations · 4 across the 11 of their papers we have counts for
6 papers · 1 filter
Exposing Blind Spots in Deep Imbalanced Regression Evaluation
Noah C. Puetz, Jens U. Brandt, Marc Hilbert +3
Deep Imbalanced Regression (DIR) addresses a common failure mode of regression models: target distributions are highly non-uniform, causing models to perform best in densely popula…
LLMs taking shortcuts in test generation: A study with SAP HANA and LevelDB
Vekil Bekmyradov, Noah C. Pütz, Thomas Bartz-Beielstein
Large Language Models (LLMs) have achieved impressive results on public benchmarks, often leading to claims of advanced reasoning and understanding. However, recent research in cog…
Physics-based Approximation and Prediction of Speedlines in Compressor Performance Maps
Abdul-Malik Akiev, Danyal Ergür, Alexander Schirger +3
Speedlines in compressor performance maps (CPMs) are critical for understanding and predicting compressor behavior under various operating conditions. We investigate a physics-base…
Multi-Task Optimization over Networks of Tasks
Julian Hatzky, Thomas Bartz-Beielstein, A. E. Eiben +1
Multi-task optimization is a powerful approach for solving a large number of tasks in parallel. However, existing algorithms face distinct limitations: Population-based methods sca…
Optimization with SpotOptim
Thomas Bartz-Beielstein
The spotoptim package implements surrogate-model-based optimization of expensive black-box functions in Python. Building on two decades of Sequential Parameter Optimization (SPO) m…
MuViS: Multimodal Virtual Sensing Benchmark
Jens U. Brandt, Noah C. Puetz, Jobel Jose George +5
Virtual sensing aims to infer hard-to-measure quantities from accessible measurements and is central to perception and control in physical systems. Despite rapid progress from firs…