Christoph Kern

Orcid: 0000-0001-7363-4299

Affiliations:
  • Ludwig Maximilian University of Munich, Germany


According to our database1, Christoph Kern authored at least 33 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Algorithms for reliable decision-making need causal reasoning.
Nat. Comput. Sci., May, 2025

Fairness in Algorithmic Profiling: The AMAS Case.
Minds Mach., March, 2025

The Value of Prediction in Identifying the Worst-Off.
CoRR, January, 2025

Correcting Annotator Bias in Training Data: Population-Aligned Instance Replication (PAIR).
CoRR, January, 2025

Location matching on shaky grounds: Re-evaluating algorithms for refugee allocation.
Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

Fares on Fairness: Using a Total Error Framework to Examine the Role of Measurement and Representation in Training Data on Model Fairness and Bias.
Proceedings of the European Workshop on Algorithmic Fairness, 2025

A Simulation Framework for Studying the Social Impacts of Algorithm-Based Refugee Matching.
Proceedings of the European Workshop on Algorithmic Fairness, 2025

Re-evaluating the role of refugee integration factors for building more equitable allocation algorithms.
Proceedings of the European Workshop on Algorithmic Fairness, 2025

Preventing Harmful Data Practices by using Participatory Input to Navigate the Machine Learning Multiverse.
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

2024
Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production.
AStA Wirtschafts und Sozialstatistisches Arch., June, 2024

Multi-Accurate CATE is Robust to Unknown Covariate Shifts.
Trans. Mach. Learn. Res., 2024

Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector.
Gov. Inf. Q., 2024

The Missing Link: Allocation Performance in Causal Machine Learning.
CoRR, 2024

Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts.
CoRR, 2024

One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Lazy Data Practices Harm Fairness Research.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Unveiling the Blindspots: Examining Availability and Usage of Protected Attributes in Fairness Datasets.
Proceedings of the 3rd European Workshop on Algorithmic Fairness, 2024

Deciding the Future of Refugees: Rolling the Dice or Algorithmic Location Assignment?
Proceedings of the 3rd European Workshop on Algorithmic Fairness, 2024

2023
Bridging the Gap: Towards an Expanded Toolkit for ML-Supported Decision-Making in the Public Sector.
CoRR, 2023

Everything, Everywhere All in One Evaluation: Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness.
CoRR, 2023

Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness.
Proceedings of the HHAI 2023: Augmenting Human Intellect, 2023

What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Ethnic Classifications in Algorithmic Decision-Making Processes.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Annotation Sensitivity: Training Data Collection Methods Affect Model Performance.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Social impacts of algorithmic decision-making: A research agenda for the social sciences.
Big Data Soc., January, 2022

Humans versus machines: Who is perceived to decide fairer? Experimental evidence on attitudes toward automated decision-making.
Patterns, 2022

Uncertainty-aware predictive modeling for fair data-driven decisions.
CoRR, 2022

2021
mcboost: Multi-Calibration Boosting for R.
Dataset, August, 2021

mcboost: Multi-Calibration Boosting for R.
J. Open Source Softw., 2021

Fairness in Algorithmic Profiling: A German Case Study.
CoRR, 2021

Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There?
CoRR, 2021


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