3 citations · 3 across the 9 of their papers we have counts for
9 papers
An Imbalanced Dataset with Multiple Feature Representations for Studying Quality Control of Next-Generation Sequencing
Philipp Röchner, Clarissa Krämer, Johannes U Mayer +3
Next-generation sequencing (NGS) is a key technique for studying the DNA and RNA of organisms. However, identifying quality problems in NGS data across different experimental setti…
ROIDS: Robust Outlier-Aware Informed Down-Sampling
Alina Geiger, Martin Briesch, Dominik Sobania +1
Informed down-sampling (IDS) is known to improve performance in symbolic regression when combined with various selection strategies, especially tournament selection. However, recen…
Transformer Semantic Genetic Programming for d-dimensional Symbolic Regression Problems
Philipp Anthes, Dominik Sobania, Franz Rothlauf
Transformer Semantic Genetic Programming (TSGP) is a semantic search approach that uses a pre-trained transformer model as a variation operator to generate offspring programs with…
We Need to Rethink Benchmarking in Anomaly Detection
Philipp Röchner, Simon Klüttermann, Kevin Kammler +3
Despite the continuous proposal of new anomaly detection algorithms and extensive benchmarking efforts, progress seems to stagnate, with only minor performance differences between…
Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection
Alina Geiger, Martin Briesch, Dominik Sobania +1
The success of lexicase selection has led to various extensions, including its combination with down-sampling, which further increased performance. However, recent work found that…
Transformer Semantic Genetic Programming for Symbolic Regression
Philipp Anthes, Dominik Sobania, Franz Rothlauf
In standard genetic programming (stdGP), solutions are varied by modifying their syntax, with uncertain effects on their semantics. Geometric-semantic genetic programming (GSGP), a…
ComfyGI: Automatic Improvement of Image Generation Workflows
Dominik Sobania, Martin Briesch, Franz Rothlauf
Automatic image generation is no longer just of interest to researchers, but also to practitioners. However, current models are sensitive to the settings used and automatic optimiz…
Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers (Extended Version)
Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello +2
Outlier detection algorithms typically assign an outlier score to each observation in a dataset, indicating the degree to which an observation is an outlier. However, these scores…
A Performance Analysis of Lexicase-Based and Traditional Selection Methods in GP for Symbolic Regression
Alina Geiger, Dominik Sobania, Franz Rothlauf
In recent years, several new lexicase-based selection variants have emerged due to the success of standard lexicase selection in various application domains. For symbolic regressio…