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Julius von Kügelgen · SciRah

Researcher profile · Semantic Scholar

Julius von Kügelgen

ETH Zürich

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Julius von Kügelgen — researcher profile on SciRah

ORCID iD 0000-0001-6469-4118Homepage

h-index: 27
Works: 46
Citations: 2,373

Most-cited papers

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel +3 more
2021Neural Information Processing Systems432 citations
Semantic Scholar
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Amir-Hossein Karimi, Julius von Kügelgen, B. Schölkopf, Isabel Valera
2020Neural Information Processing Systems226 citations
Semantic Scholar
Independent mechanism analysis, a new concept?
Luigi Gresele, Julius von Kügelgen, Vincent Stimper, B. Schölkopf +1 more
2021Neural Information Processing Systems135 citations
Semantic Scholar
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen, M. Besserve, Wendong Liang, Luigi Gresele +4 more
2023Neural Information Processing Systems130 citations Open access
Semantic Scholar
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen, Umang Bhatt, Amir-Hossein Karimi, Isabel Valera +2 more
2020AAAI Conference on Artificial Intelligence113 citations Open access
Semantic Scholar
Multi-View Causal Representation Learning with Partial Observability
Ding-Ling Yao, Dan-Ru Xu, Sébastien Lachapelle, Sara Magliacane +4 more
2023International Conference on Learning Representations100 citations
Semantic Scholar
Probable Domain Generalization via Quantile Risk Minimization
Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen +3 more
2022Neural Information Processing Systems100 citations Open access
Semantic Scholar
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain
Lukas Schott, Julius von Kügelgen, F. Träuble, Peter Gehler +5 more
2021International Conference on Learning Representations87 citations
Semantic Scholar
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Ronan Perry, Julius von Kügelgen, B. Schölkopf
2022Neural Information Processing Systems86 citations Open access
Semantic Scholar
Complex interlinkages, key objectives, and nexuses among the Sustainable Development Goals and climate change: a network analysis.
F. Laumann, Julius von Kügelgen, Thiago Kanashiro Uehara, Mauricio Barahona
2022Lancet Planetary Health77 citations
Semantic Scholar
Causal Component Analysis
Wendong Liang, Armin Keki'c, Julius von Kügelgen, Simon Buchholz +3 more
2023Neural Information Processing Systems65 citations Open access
Semantic Scholar
From Statistical to Causal Learning
B. Schölkopf, Julius von Kügelgen
2022arXiv.org59 citations Open access
Semantic Scholar
Provably Learning Object-Centric Representations
Jack Brady, R. Zimmermann, Yash Sharma, B. Schölkopf +2 more
2023International Conference on Machine Learning58 citations Open access
Semantic Scholar
xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers
Julius von Kügelgen, Julius von Kügelgen
2022xxAI@ICML55 citations Open access
Semantic Scholar
Towards causal generative scene models via competition of experts
Julius von Kügelgen, Ivan Ustyuzhaninov, Peter Gehler, M. Bethge +1 more
2020arXiv.org54 citations
Semantic Scholar
Active Bayesian Causal Inference
C. Toth, Lars Lorch, Christian Knoll, A. Krause +3 more
2022Neural Information Processing Systems53 citations Open access
Semantic Scholar
A Sparsity Principle for Partially Observable Causal Representation Learning
Dan-Ru Xu, Ding-Ling Yao, Sébastien Lachapelle, Perouz Taslakian +3 more
2024International Conference on Machine Learning44 citations
Semantic Scholar
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Gehler +3 more
2021International Conference on Learning Representations39 citations
Semantic Scholar
Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects
Julius von Kügelgen, Luigi Gresele, B. Schölkopf
2020IEEE Transactions on Artificial Intelligence39 citations Open access
Semantic Scholar
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya +3 more
2021Conference on Empirical Methods in Natural Language Processing38 citations Open access
Semantic Scholar
A bacterial size law revealed by a coarse-grained model of cell physiology
F. Bertaux, Julius von Kügelgen, S. Marguerat, V. Shahrezaei
2020PLoS Comput. Biol.38 citations Open access
Semantic Scholar
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
P. Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen +5 more
2022Neural Information Processing Systems35 citations Open access
Semantic Scholar
Causal Inference Through the Structural Causal Marginal Problem
Luigi Gresele, Julius von Kügelgen, Jonas M. Kubler, Elke Kirschbaum +2 more
2022International Conference on Machine Learning32 citations
Semantic Scholar
Backtracking Counterfactuals
Julius von Kügelgen, Abdirisak Mohamed, Sander Beckers
2022CLEaR31 citations Open access
Semantic Scholar
Unsupervised Object Learning via Common Fate
Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello +5 more
2021CLEaR30 citations
Semantic Scholar
Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features
Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica +2 more
2023Neural Information Processing Systems29 citations Open access
Semantic Scholar
DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kügelgen, Armin Keki'c +3 more
2022International Conference on Learning Representations27 citations Open access
Semantic Scholar
Interaction Asymmetry: A General Principle for Learning Composable Abstractions
Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz +2 more
2024arXiv.org22 citations
Semantic Scholar
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
Julius von Kügelgen, Paul K. Rubenstein, B. Schölkopf, Adrian Weller
2019arXiv.org22 citations
Semantic Scholar
Backward-Compatible Prediction Updates: A Probabilistic Approach
F. Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello +2 more
2021Neural Information Processing Systems20 citations
Semantic Scholar
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations
Cian Eastwood, Julius von Kügelgen, Linus Ericsson, D. Bouchacourt +3 more
2023arXiv.org19 citations
Semantic Scholar
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features
Julius von Kügelgen, A. Mey, M. Loog
2018International Conference on Artificial Intelligence and Statistics15 citations
Semantic Scholar
Identifiable Causal Representation Learning: Unsupervised, Multi-View, and Multi-Environment
Julius von Kügelgen
2024arXiv.org13 citations
Semantic Scholar
Deep Backtracking Counterfactuals for Causally Compliant Explanations
Klaus-Rudolf Kladny, Julius von Kügelgen, B. Schölkopf, Michael Muehlebach
2023Trans. Mach. Learn. Res.13 citations Open access
Semantic Scholar
Kernel-Based Independence Tests for Causal Structure Learning on Functional Data
F. Laumann, Julius von Kügelgen, Junhyung Park, B. Schölkopf +1 more
2023Entropy13 citations Open access
Semantic Scholar
Evaluating vaccine allocation strategies using simulation-assisted causal modeling
Armin Kekić, Jonas Dehning, Luigi Gresele, Julius von Kügelgen +2 more
2023Patterns10 citations Open access
Semantic Scholar
Kernel Two-Sample and Independence Tests for Nonstationary Random Processes
F. Laumann, Julius von Kügelgen, Mauricio Barahona
2020Engineering Proceedings8 citations Open access
Semantic Scholar
Independent Mechanism Analysis and the Manifold Hypothesis
Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, M. Besserve +1 more
2023arXiv.org6 citations
Semantic Scholar
From Pixels to Components: Eigenvector Masking for Visual Representation Learning
Alice Bizeul, T. Sutter, Alain Ryser, B. Schölkopf +2 more
2025arXiv.org4 citations
Semantic Scholar
Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals
F. Laumann, Julius von Kügelgen, Mauricio Barahona
20204 citations
Semantic Scholar
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen, N. Agarwal, Jakob Zeitler, Afsaneh Mastouri +1 more
2021arXiv.org3 citations
Semantic Scholar
Causal Effect Estimation from Observational and Interventional Data Through Matrix Weighted Linear Estimators
Klaus-Rudolf Kladny, Julius von Kügelgen, B. Schölkopf, Michael Muehlebach
2023Conference on Uncertainty in Artificial Intelligence2 citations Open access
Semantic Scholar
Anchor PCA
Benedikt Seiter, Anya Fries, Julius von Kügelgen, Jonas Peters
2026arXiv.org1 citations
Semantic Scholar
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective"
Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, M. Besserve +1 more
2022arXiv.org1 citations
Semantic Scholar
A Mathematical Model for the Kinetics of the MalFGK[Formula: see text] Maltose Transporter.
R. Hiller, Julius von Kügelgen, Huan Bao, Franck Duong van Hoa +1 more
2020Bulletin of Mathematical Biology1 citations
Semantic Scholar
Interaction Asymmetry: A General Principle for Learning Composable Abstractions
Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz +2 more
2025International Conference on Learning Representations0 citations
Semantic Scholar

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