Causal Analysis of Feedback Systems

Project Information

CAFES

Grant agreement ID: 639466

DOI

10.3030/639466

Project closed

EC signature date 8 May 2015

Start date 1 September 2015

End date 31 August 2020

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 405 652,00

EU contribution

€ 1 405 652,00

Coordinated by

UNIVERSITEIT VAN AMSTERDAM
Netherlands

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Publications

Conference proceedings (10)

Algebraic Equivalence of Linear Structural Equation Models

Author(s): Thijs van Ommen, Joris M. Mooij
Published in: Proceedings of the 33rd Annual Conference on Uncertainty in Artificial Intelligence, Issue UAI 2017, 2017
Publisher: Association for Uncertainty in Artificial Intelligence

Causal Effect Inference with Deep Latent-Variable Models

Author(s): Louizos, Christos; Shalit, Uri; Mooij, Joris; Sontag, David; Zemel, Richard; Welling, Max
Published in: Advances in Neural Information Processing Systems 30, Issue NeurIPS 2017, 2017, Page(s) 6446-6456
Publisher: Curran Associates, Inc.

Causal Consistency of Structural Equation Models

Author(s): Rubenstein, Paul K.; Weichwald, Sebastian; Bongers, Stephan; Mooij, Joris M.; Janzing, Dominik; Grosse-Wentrup, Moritz; Schölkopf, Bernhard
Published in: Proceedings of the 33rd Annual Conference on Uncertainty in Artificial Intelligence, Issue UAI 2017, 2017
Publisher: Association for Uncertainty in Artificial Intelligence

From Deterministic ODEs to Dynamic Structural Causal Models

Author(s): Rubenstein, Paul K.; Bongers, Stephan; Schoelkopf, Bernhard; Mooij, Joris M.
Published in: Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence (UAI-18), Issue UAI 2018, 2018
Publisher: Association for Uncertainty in Artificial Intelligence

An Upper Bound for Random Measurement Error in Causal Discovery

Author(s): Tineke Blom, Anna Klimovskaia, Sara Magliacane, Joris M. Mooij
Published in: Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence (UAI-18), Issue UAI 2018, 2018
Publisher: Association for Uncertainty in Artificial Intelligence

Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders

Author(s): Patrick Forré, Joris M. Mooij
Published in: Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence (UAI-18), Issue UAI 2018, 2018
Publisher: Association for Uncertainty in Artificial Intelligence

Beyond Structural Causal Models: Causal Constraints Models

Author(s): Tineke Blom, Stephan Bongers, Joris M. Mooij
Published in: Proceedings of the 35th Annual Conference on Uncertainty in Artificial Intelligence, Issue UAI 2019, 2019
Publisher: AUAI Press

Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias

Author(s): Patrick Forré, Joris M. Mooij
Published in: Proceedings of the 35th Annual Conference on Uncertainty in Artificial Intelligence, Issue UAI 2019, 2019
Publisher: AUAI Press

Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Author(s): Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
Published in: Advances in Neural Information Processing Systems (NeurIPS-2018), Issue NeurIPS 2018, 2018, Page(s) 10869-10879
Publisher: Curran Associates, Inc.

Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles

Author(s): Mooij, Joris M.; Claassen, Tom
Published in: Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), Issue 124, 2020, Page(s) 1159-1168
Publisher: Proceedings of Machine Learning Research