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2020 – today
- 2024
[c5]Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge:
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CLeaR 2024: 843-867- [i5]Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge:
Causal discovery with endogenous context variables. CoRR abs/2412.04981 (2024) - 2023
- [c4]Jonas Wahl, Urmi Ninad, Jakob Runge:
Vector Causal Inference between Two Groups of Variables. AAAI 2023: 12305-12312 - [c3]Wiebke Günther, Urmi Ninad, Jakob Runge:
Causal Discovery for time series from multiple datasets with latent contexts. UAI 2023: 766-776 - [c2]Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge:
Increasing effect sizes of pairwise conditional independence tests between random vectors. UAI 2023: 879-889 - [i4]Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge:
Discovering Causal Relations and Equations from Data. CoRR abs/2305.13341 (2023) - [i3]Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge:
Projecting infinite time series graphs to finite marginal graphs using number theory. CoRR abs/2310.05526 (2023) - [i2]Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge:
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CoRR abs/2311.02695 (2023) - [i1]Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge:
Invariance & Causal Representation Learning: Prospects and Limitations. CoRR abs/2312.03580 (2023) - 2022
- [c1]Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge:
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery. NeurIPS 2022
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