Articles by Ulrike Von Luxburg | Synthical

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49

Rethinking Explainable Machine Learning as Applied Statistics

3 February 2025 by Sebastian Bordt and others

Machine Learning

How Much Can We Forget about Data Contamination?

30 January 2025 by Sebastian Bordt and others

Machine Learning, Artificial Intelligence

Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension

6 November 2024 by Moritz Haas and others

Machine Learning, Statistics Theory

Disentangling Interactions and Dependencies in Feature Attribution

31 October 2024 by Gunnar König and others

Machine Learning

Auditing Local Explanations is Hard

18 July 2024 by Robi Bhattacharjee and Ulrike Von Luxburg

Machine Learning

Relating graph auto-encoders to linear models

30 November 2023 by Solveig Klepper and Ulrike Von Luxburg

Machine Learning

ChatGPT Participates in a Computer Science Exam

22 March 2023 by Sebastian Bordt and Ulrike Von Luxburg

Computation and Language, Computers and Society

AI for Science: An Emerging Agenda

7 March 2023 by Philipp Berens and others

Artificial Intelligence, Computers and Society

Pitfalls of Climate Network Construction: A Statistical Perspective

17 November 2022 by Moritz Haas and others

Machine Learning

A Consistent Estimator for Confounding Strength

3 November 2022 by Luca Rendsburg and others

Machine Learning

The Manifold Hypothesis for Gradient-Based Explanations

15 June 2022 by Sebastian Bordt and others

Machine Learning, Computer Vision and Pattern Recognition

Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts

10 May 2022 by Sebastian Bordt and others

Machine Learning, Artificial Intelligence

Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference

7 March 2022 by Luca Rendsburg and others

Machine Learning

Interpolation and Regularization for Causal Learning

18 February 2022 by Leena Chennuru Vankadara and others at

Technical University of Munich

Machine Learning

A Bandit Model for Human-Machine Decision Making with Private Information and Opacity

11 November 2021 by Sebastian Bordt and Ulrike Von Luxburg

Machine Learning

Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models

18 October 2021 by Leena Chennuru Vankadara and others

Machine Learning

Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees

29 September 2021 by Solveig Klepper and others

Machine Learning

Specialists Outperform Generalists in Ensemble Classification

9 July 2021 by Sascha Meyen and others

Machine Learning

Advancing Research on Unconscious Priming: When can Scientists Claim an Indirect Task Advantage?

7 June 2021 by Sascha Meyen and others

Group Decisions based on Confidence Weighted Majority Voting

7 June 2021 by Sascha Meyen and others

Looking Deeper into Tabular LIME

18 September 2020 by Damien Garreau and Ulrike Von Luxburg

Machine Learning, Artificial Intelligence

Large scale ordinal embedding: training neural networks with structure-free inputs

23 July 2020 by Leena Chennuru Vankadara and others

Machine Learning

Explaining the Explainer: A First Theoretical Analysis of LIME

13 January 2020 by Damien Garreau and Ulrike Von Luxburg

Machine Learning

Estimation of perceptual scales using ordinal embedding

21 August 2019 by Siavash Haghiri and others

Machine Learning, Computer Vision and Pattern Recognition

Comparison-Based Framework for Psychophysics: Lab versus Crowdsourcing

26 July 2019 by Siavash Haghiri and others

Machine Learning

Uncertainty Estimates for Ordinal Embeddings

27 June 2019 by Michael Lohaus and others

Machine Learning

Foundations of Comparison-Based Hierarchical Clustering

12 June 2019 by Debarghya Ghoshdastidar and others

Machine Learning

Boosting for Comparison-Based Learning

29 May 2019 by Michaël Perrot and Ulrike Von Luxburg

Machine Learning

Practical methods for graph two-sample testing

30 November 2018 by Debarghya Ghoshdastidar and Ulrike Von Luxburg

Machine Learning

Comparison-Based Random Forests

18 June 2018 by Siavash Haghiri and others

Machine Learning

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Machine Learning Statistics Theory Data Structures and Algorithms Methodology Artificial Intelligence Applications Computers and Society Computer Vision and Pattern Recognition Computation and Language Digital Libraries Social and Information Networks Neurons and Cognition Probability