- Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey M. Plis:
Causal Learning through Deliberate Undersampling. CLeaR 2023: 518-530 - Eric V. Strobl, Thomas A. Lasko:
Generalizing Clinical Trials with Convex Hulls. CLeaR 2023: 197-221 - Eric V. Strobl, Thomas A. Lasko:
Sample-Specific Root Causal Inference with Latent Variables. CLeaR 2023: 895-915 - Matthias Tangemann, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, Bernhard Schölkopf:
Unsupervised Object Learning via Common Fate. CLeaR 2023: 281-327 - Abhishek Kumar Umrawal:
Leveraging Causal Graphs for Blocking in Randomized Experiments. CLeaR 2023: 222-242 - Jonas Bernhard Wildberger, Siyuan Guo, Arnab Bhattacharyya, Bernhard Schölkopf:
On the Interventional Kullback-Leibler Divergence. CLeaR 2023: 328-349 - Shiqing Yu, Mathias Drton, Ali Shojaie:
Directed Graphical Models and Causal Discovery for Zero-Inflated Data. CLeaR 2023: 27-67 - Jakob Zeitler, Athanasios Vlontzos, Ciarán Mark Gilligan-Lee:
Non-parametric identifiability and sensitivity analysis of synthetic control models. CLeaR 2023: 850-865 - Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas:
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CLeaR 2023: 88-121 - Mihaela van der Schaar, Cheng Zhang, Dominik Janzing:
Conference on Causal Learning and Reasoning, CLeaR 2023, 11-14 April 2023, Amazon Development Center, Tübingen, Germany, April 11-14, 2023. Proceedings of Machine Learning Research 213, PMLR 2023 [contents]