1 citations · 1 across the 7 of their papers we have counts for
8 papers
RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data
Xuan Zhao, Lena Krieger, Zhuo Cao +3
Counterfactual explanations (CFs) help understand machine learning models by identifying minimal input changes that would lead to alternative model outcomes. Recent work demonstrat…
Residual-Space Evolutionary Optimization via Flow-based Generative Models
Zhuo Cao, Lena Krieger, Fernanda Nader +3
Data editing with generative methods typically requires differentiable objectives and gradient-based search. However, these assumptions break down in flow-based settings, where edi…
Counterfactual Transport Flows for Offline Conservative Trajectory Refinement
Lena Krieger, Xuan Zhao, Zhuo Cao +3
Offline reinforcement learning (RL) offers a path to policy improvement from logged data alone, using historical returns or other measurable outcomes as world feedback. A key diffi…
ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material
Pernille Matthews, Lena Krieger, Tommaso Amico +3
Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they are not directly applicable…
DCFO: Density-Based Counterfactuals for Outliers -- Additional Material
Tommaso Amico, Pernille Matthews, Lena Krieger +2
Outlier detection identifies data points that significantly deviate from the majority of the data distribution. Explaining outliers is crucial for understanding the underlying fact…
LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching
Zhuo Cao, Xuan Zhao, Lena Krieger +2
The growing integration of machine learning (ML) and artificial intelligence (AI) models into high-stakes domains such as healthcare and scientific research calls for models that a…
Galaxy Morphology Classification with Counterfactual Explanation
Zhuo Cao, Lena Krieger, Hanno Scharr +1
Galaxy morphologies play an essential role in the study of the evolution of galaxies. The determination of morphologies is laborious for a large amount of data giving rise to machi…
Internal Evaluation of Density-Based Clusterings with Noise
Anna Beer, Lena Krieger, Pascal Weber +3
Being able to evaluate the quality of a clustering result even in the absence of ground truth cluster labels is fundamental for research in data mining. However, most cluster valid…