Julius von Kgelgen
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
14
Venues
6
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
14 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Interaction Asymmetry: A General Principle for Learning Composable Abstractions. | Jack Brady, Julius von Kgelgen, Sbastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel |
| 2024 | ICLR | Multi-View Causal Representation Learning with Partial Observability. | Dingling Yao, Danru Xu, Sbastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kgelgen, Francesco Locatello |
| 2024 | ICML | A Sparsity Principle for Partially Observable Causal Representation Learning. | Danru Xu, Dingling Yao, Sbastien Lachapelle, Perouz Taslakian, Julius von Kgelgen, Francesco Locatello, Sara Magliacane |
| 2023 | ICLR | DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. | Cian Eastwood, Andrei Liviu Nicolicioiu, Julius von Kgelgen, Armin Kekic, Frederik Truble, Andrea Dittadi, Bernhard Schlkopf |
| 2023 | ICML | Provably Learning Object-Centric Representations. | Jack Brady, Roland S. Zimmermann, Yash Sharma, Bernhard Schlkopf, Julius von Kgelgen, Wieland Brendel |
| 2023 | UAI | Causal effect estimation from observational and interventional data through matrix weighted linear estimators. | Klaus-Rudolf Kladny, Julius von Kgelgen, Bernhard Schlkopf, Michael Muehlebach |
| 2022 | AAAI | On the Fairness of Causal Algorithmic Recourse. | Julius von Kgelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schlkopf |
| 2022 | ICLR | You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. | Osama Makansi, Julius von Kgelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schlkopf |
| 2022 | ICLR | Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. | Lukas Schott, Julius von Kgelgen, Frederik Truble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schlkopf, Francesco Locatello, Wieland Brendel |
| 2022 | ICML | Causal Inference Through the Structural Causal Marginal Problem. | Luigi Gresele, Julius von Kgelgen, Jonas M. Kbler, Elke Kirschbaum, Bernhard Schlkopf, Dominik Janzing |
| 2021 | EMNLP | Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. | Zhijing Jin, Julius von Kgelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schlkopf |
| 2020 | ICML | Towards Causal Algorithmic Recourse. | Amir-Hossein Karimi, Julius von Kgelgen, Bernhard Schlkopf, Isabel Valera |
| 2020 | UAI | Semi-supervised learning, causality, and the conditional cluster assumption. | Julius von Kgelgen, Alexander Mey, Marco Loog, Bernhard Schlkopf |
| 2019 | AISTATS | Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features. | Julius von Kgelgen, Alexander Mey, Marco Loog |