Evaluating vaccine allocation strategies using simulation-assisted causal modelling. - Armin Kekic; Jonas Dehning; Luigi Gresele; Julius von Kügelgen; Viola Priesemann; Bernhard Schölkopf (CoRR, 2022)

DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability. - Cian Eastwood; Andrei Liviu Nicolicioiu; Julius von Kügelgen; Armin Kekic; Frederik Träuble; Andrea Dittadi; Bernhard Schölkopf (ICLR, 2023)

Nonparametric Identifiability of Causal Representations from Unknown Interventions. - Julius von Kügelgen; Michel Besserve; Wendong Liang; Luigi Gresele; Armin Kekic; Elias Bareinboim; David M. Blei; Bernhard Schölkopf (NeurIPS, 2023)

Causal Component Analysis. - Wendong Liang; Armin Kekic; Julius von Kügelgen; Simon Buchholz; Michel Besserve; Luigi Gresele; Bernhard Schölkopf (NeurIPS, 2023)

Deep Learning based Forecasting: a case study from the online fashion industry. - Manuel Kunz; Stefan Birr; Mones Raslan; Lei Ma; Zhen Li; Adèle Gouttes; Mateusz Koren; Tofigh Naghibi; Johannes Stephan; Mariia Bulycheva; Matthias Grzeschik; Armin Kekic; et al. (CoRR, 2023)

Evaluating vaccine allocation strategies using simulation-assisted causal modeling. - Armin Kekic; Jonas Dehning; Luigi Gresele; Julius von Kügelgen; Viola Priesemann; Bernhard Schölkopf (Patterns, 2023)

Targeted Reduction of Causal Models. - Armin Kekic; Bernhard Schölkopf; Michel Besserve (UAI, 2024)

Estimating Joint interventional distributions from marginal interventional data. - Sergio Hernan Garrido Mejia; Elke Kirschbaum; Armin Kekic; Atalanti-Anastasia Mastakouri (CoRR, 2024)

Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models. - Armin Kekic; Sergio Hernan Garrido Mejia; Bernhard Schölkopf (CoRR, 2025)

Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies. - Armin Kekic; Jan Schneider 007; Dieter Büchler; Bernhard Schölkopf; Michel Besserve (CoRR, 2025)