Causality Reading Club

The Causality Reading group is weekly event organized internally by the Causality group led by prof. Joris Mooij. Due to the global pandemic, this is held online over Zoom. Anyone interested in the field is free to participate, you can get information on how to join by sending an email to aawmdekroon (at)


June 4, 14:00, Zoom, A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery by Boeken and Mooij, Philip Boeken
June 4, 14:00, Zoom, A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms by Bengio et. al., Noud
May 27, 14:00, Zoom, Constraint-Based Causal Discovery In The Presence Of Cycles by Joris Mooij and Tom Claassen, Joris
May 14, 14:00, Zoom, Designing Data Augmentation for Simulating Interventions by Maximilian Ilse\, Jakub Tomczak, and Patrick Forré\, Maximilian
May 7, 14:00, Zoom, Causal Discovery in the Presence of Missing Data by Tu et. al., Philip
Apr 30, 14:00, Zoom, Learning stable and predictive structures in kinetic systems, Stephan
Apr 23, 14:00, Zoom, A correspondence principle for simultaneous equation models, Tineke
Apr 9, 14:00, Zoom, Causally Correct Partial Models for Reinforcement Learning, Noud
Apr 2, 14:00, Zoom, Out-of-Distribution Generalization via Risk Extrapolation, Patrick
Mar 19, 14:00, Zoom, Constraint-based Causal Structure Learning with Consistent Separating Sets, Philip
Mar 5, 14:00, F2.02, Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations, Noud
Jan 14, 13:00, C3.163, Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems by Ness et al., Tineke


Dec 17, 13:00, C3.163, A Bayesian nonparametric test for conditional independence by Onur Teymur et al., Patrick
Dec 3, 13:00, C3.163, Causal Regularization by Dominik Janzing, Philip
Nov 26, 13:00, C3.163, Adjacency-Faithfulness and Conservative Causal Inference by Joseph Ramsey et al., Alexander
Oct 22, 13:00, C3.163, Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation by Ruibo Tu et al., Noud
Sep 24, 13:00, C3.163, Approximate Causal Abstraction by Sander Beckers et al., Stephan
Sep 10, 13:00, C3.163, Active Causal Discovery by Predicting Counterfactual Outcomes, Aron Hammond
Aug 27,13:00, C3.163, Invariant Risk Minimization by Martin Arjovsky et al., Patrick
Aug 13,13:00,C3.163, Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach by Tikka et al., Philip
July 16, 13:00,C3.163, Density estimation using Real NVP by Laurent Dinh et al., Stephan
July 2, 13:00,C3.163, Abstracting Causal Models by Sander Beckers and  Joseph Y. Halpern, Tineke
June 18,13:00,C3.163, Causal Confusion in Imitation Learning by De Haan et al., Noud
June 11,13:00,C3.163, Orthogonal Structure Search for Efficient Causal Discovery from Observational Data by Raj et al., Phillip
May 28,13:00,C3.163, Cancelled, Cancelled
May 14,13:00,C3.163, Learning Disentangled Representations with Semi-Supervised Deep Generative Models by Siddharth et al., Stephan
Apr 30,13:00,C3.163, Structural Causal Bandits: Where to Intervene? by Lee and Bareinboim, Noud
Apr 16,13:00,C3.163, Defining Network Topologies that Can Achieve Biochemical Adaptation by Ma et al. and Perfect and Near-Perfect Adaptation in Cell Signaling by Ferrell , Tineke
Apr 2,13:00,C3.163, Cancelled, Cancelled
Mar 19 26,13:00,C3.163, Dynamic Chain Graph Models for Ordinal Time Series Data by Behrouzi et al., Pariya Behrouzi
Mar 5,13:00,C3.163, Some of his own work, Thijs
Feb 26,13:00,C3.163, Cancelled, Cancelled
Feb 19,13:00,C3.163, Canceled, Cancelled
Feb 12,13:00,C3.163, Causal Reasoning from Meta-reinforcement Learning by Dasgupta et al., Noud
Feb 5,13:00,A1.14., Small workshop with presentations (mostly) on counterfactuals by Robert van Rooij\, Katrin Schultz\, and Joris Mooij, Joris
Jan 29,13:00,C2.109, Cause-Effect Deep Information Bottleneck For Incomplete Covariates by Parbhoo et al. (2018), Stephan
Jan 15,13:00,C3.163,Equality of Opportunity in Classification: A Causal Approach by Junzhe Zhang and Elias Bareinboim (2018), Tineke


Dec 18,13:00,C2.109,Learning Predictive Models That Transport by Subbaswamy et al. (2018),Thijs
Dec 11,13:00,C2.109,Cancelled,
Dec 4,13:00,C3.163,Woulda\, Coulda\, Shoulda: Counterfactually-Guided Policy Search by Buesing et al. (2018),Noud
Nov 27,13:00,C2.109,Multi-domain Causal Structure Learning in Linear Systems by Ghassami et al. (2018),Philip
Nov 20,13:00,C3.163,Multiple Causal Inference with Latent Confounding by Ranganath and Perotte (2018),Stephan
Nov 13,13:00,C3.163,A Constraint-Based Algorithm For Causal Discovery with Cycles\, Latent Variables and Selection Bias by Strobl (2018),Patrick
Nov 6,14:00,C3.163,TBD,Tineke
Oct 30,14:00,C3.163,TBD,Joris
Oct 23,14:00,C3.163,Model selection and local geometry by Evans (2018),Thijs
Oct 16,14:00,C3.163,Learning Functional Causal Models with Generative Neural Networks by Goudet et al. (2017),Philip
Oct 9,14:00,C3.163,Causal Learning for Partially Observed Stochastic Dynamical Systems by Mogensen et al. (2018),Stephan
Oct 2,14:00,C3.163,The inflation technique solves completely the classical inference problem by Navascues and Wolf (2017),Patrick
Sep 25,14:00,C2.109,The Inflation Technique for Causal Inference with Latent Variables by Wolf et al. (2018) [part 2],Tineke
Sep 18,14:00,C3.146,The Inflation Technique for Causal Inference with Latent Variables by Wolf et al. (2018) [part 1],Tineke
Sep 11,14:00,C3.163,The Inferelator by Bonneau et al. (2016),Joris
Jul 12,15:00,C3.146,Counterfactual Risk Minimization: Learning from Logged Bandit Feedback (2015) by Swaminathan and Joachims ,Philip
Jun 28,15:00,C3.146,Causality and model abstraction by Iwasaki and Simon (1994) [part 2],Stephan
Jun 14,15:00,C3.146,The blessing of multiple causes by Wang and Blei (2018),Patrick
Jun 7,15:00,C3.146,Paper Draft,Thijs
May 24,15:00,C3.146,The Blessings of Multiple Causes by Wang and Blei (2018,Patrick
May 17,15:00,C3.146,Information Processing Features Can Detect Behavioral Regimes of Dynamical Systems by Quax et al. (2017),Rick Quax
Apr 26,15:00,C3.146,Causality and model abstraction by Iwasaki and Simon (1994) [part 1],Tineke
Apr 12,15:00,C3.146,Joint Causal Inference from Multiple Datasets by et al. (2018),Joris
Apr 5,15:00,C3.146,Efficient Structure Learning of Bayesian Networks using Constraints by de Campos and Ji (2011),Thijs
Mar 29,15:00,C3.146,Consistency Guarantees for Permutation-Based Causal Inference Algorithms by Solus et al. (2017) ,Philip
Mar 2,15:00,C3.146,On the latent space of Wasserstein Auto-Encoders by Rubinstein et al . (2018),Stephan
Mar 1,15:00,C3.146,Draft reviews,All
Feb 15,15:00,C3.146, Predictive Independence Testing\, Predictive Conditional Independence Testing\, and Predictive Graphical Modelling by Burkart and Király (2017),Patrick
Jan 11,15:00,C3.146,Extended Conditional Independence and Applications in Causal Inference by Constantinou and Dawid (2017),Patrick


Dec 21, 15:00, C3.146,Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry by Lun et al.(2017),Tineke Blom
Nov 16, 15:00, C3.146,Causal inference using the algorithmic Markov condition by Janzing and Schoelkopf (2008) and Causal Markov condition for submodular information measures by Steudel et al. (2010),Patrick Forré
Nov 9, 15:00, C3.146,Telling Cause from Effect using MDL-based Local and Global Regression by Marx and Vreeken (2017),Thijs van Ommen
Nov 2, 15:00, C3.146,Implicit Causal Models for Genome-wide Association Studies by Tran and Blei (2017),Joris Mooij
Oct 28, 15:00, C3.146,Structure Learning of Linear Gaussian Structural Equation Models with Weak Edges by Eigenmann et al. (2017),Tineke Blom
Oct 12, 15:00, C3.146,Identifying Best Interventions through Online Importance Sampling by Sen et al. (2017),Philip Versteeg
Sep 28, 15:00, C3.146,Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information by Jakob Runge (2017),Patrick Forré
Sep 21, 15:00, C3.146,Avoiding Discrimination through Causal Reasoning by Kilbertus et al.  (2017), Sara Magliacane
Sep 14, 15:00, C3.146,CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training by Kocaoglu et al. (2017),Patrick Forré
Aug 25, 14:00, C3.146,Paper draft, Patrick Forré
Aug 18, 14:00, C3.146,Ch5-8 of Counterfactual Reasoning and Learning Systems by Bottou et al. (2013),Philip Versteeg
Aug 11, 14:00, C3.146,Ch1-4 of Counterfactual Reasoning and Learning Systems by Bottou et al. (2013),Philip Versteeg
Jul 28, 14:00, C3.146,Discovering Causal Signals in Images by Lopez-Paz et al. (2017),Patrick Forré
Jul 21, 14:00, C3.146,Margins of discrete Bayesian networks by Evans (preprint),Thijs van Ommen
Jul 14, 14:00, C3.146, Revisiting Classifier Two-Sample Tests by D. Lopez-Paz and M. Oquab (2016), Stephan Bongers
Jul 7, 14:00, C3.146,Causal Discovery in the Presence of Measurement Error: Identifiability Conditions by Zhang (2017),Tineke Blom
Jun 16, 14:00, C3.146,Zhang et al. (2013)\, Zhang et al. (2015) and Gong et al. (2016),Tineke\, Stephan and Thijs
May 12, 14:00, C3.146,On Causal and Anticausal Learning by Scholkopf et al (2012),Sara Magliacane
Mar 17, 14:00, C3.146,Paper draft,Stephan Bongers
Mar 10, 14:00, C3.146,Strong completeness and faithfulness in Bayesian networks by Meek (1995),Joris Mooij
Mar 3, 14:00, C3.146,Unifying Markov Properties for Graphical Models by Lauritzen and Sadeghi (preprint),Patrick Forré
Feb 24, 14:00, C3.146,Causal Bandits: Learning Good Interventions via Causal Inference by Lattimore\, Lattimore and Reid (2016),Stephan Bongers
Feb 17, 14:00, C3.146,Bandits with Unobserved Confounders: A Causal Approach by Bareinboim\, Forney and Pearl (2016),Philip Versteeg
Feb 10, 14:00, C3.146, Joint Causal Inference (2016) by Magliacane\, Claassen and Mooij,Sara Magliacane
Feb 3, 14:00, C3.146, Paper draft,Christos Louizos
Jan 27, 14:00, C3.146,Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models (2006) by Shpitser and Pearl,Patrick Forré
Jan 13, 14:00, C3.146, Causal inference and the data-fusion problem by Bareinboim and Pearl (2016),Philip Versteeg


Jan 08,14:30,C3.146,Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing by Benjamini and Hochberg,Philip Versteeg,
Feb 05, 14:00,C3.146,Causation Prediction and Search (chapters 1&2) by Spirtes and Glymour and Scheines,Joris Mooij
Feb 12, 14:00,C3.146,Causation Prediction and Search (chapter 3) by Spirtes and Glymour and Scheines,Alexander Ly
Feb 19, 14:00,C3.146,Causation Prediction and Search (3.5 – 3.9) by Spirtes and Glymour and Scheines,Alexander Ly
Feb 26, 14:00,C3.146,Causation Prediction and Search (chapter 4) by Spirtes and Glymour and Scheines,Thijs van Ommen
Mar 4, 14:00,C3.146,Causation Prediction and Search (chapter 5.1-5.4) by Spirtes and Glymour and Scheines,Stephan Bongers
Mar 11, 14:00,C3.146,Causation Prediction and Search (chapter 5.5-5.10) by Spirtes and Glymour and Scheines,Philip Versteeg
Mar 18, 14:00,C3.146,Causation Prediction and Search (chapter 6) by Spirtes and Glymour and Scheines,Sara Magliacane
Apr 15, 14:00,C3.146,Causation Prediction and Search (chapter 7) by Spirtes and Glymour and Scheinces,Joris Mooij
Apr 22, 14:00,C3.146,Inferring the Causal Direction Privately by Kusner and Sun and Sridharan and Weinberger,Mijung Park
Apr 29, 14:00,C3.146,On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias by Zhang (2008),Joris Mooij
May 13, 14:00,C3.146, Causal inference using invariant prediction: identification and confidence intervals by Peters and Bühlmann and Meinshausen (2016),Alexander Ly
May 20, 14:00,C3.146, Quantifying Causal Influences (2012) by Janzing and Balduzzi and Grosse-Wentrup and Schölkopf, Rick Quax
May 27, 14:00,C3.146,Extending Factor Graphs so as to Unify Directed and Undirected Graphical Models by Frey (2003) and Causality with Gates (2012) by Winn, Sara Magliacane
Jul 1, 14:00,C3.146,Stephan’s draft on Markov properties of graphical representations of acyclic structural causal models,Stephan Bongers
Jul 8, 14:00, C3.146, The central role of the propensity score in observational studies for causal effects (1983) by Rosenbaum and Rubin, Thomas Klaus
Jul 22, 14:00, C3.146, Learning Optimal Interventions by Mueller and Reshef and Du and Jaakkola, Mijung Park
Jul 29, 14:00, C3.146, ICML 2016 Tutorial Causal Inference for Observational Studies by David Sontag and Uri Shalit, Joris Mooij
Aug 05, 14:00, C3.146, Causality Video Club,
Aug 12, 14:00, C3.146, Half-trek criterion for generic identifiability of linear structural equation models by Foygel and Draisma and Drton, Thijs van Ommen
Aug 19, 14:00, C3.146, Graphs for Margins of Bayesian Networks (2016) by Robin Evans, Patrick Forré
August 26, 14:00, C3.146, Estimating and Controlling the False Discovery Rate for the PC Algorithm Using Edge-Specific P-Values (2016) by Strobl and Spirtes and Visweswaran, Sara Magliacane
Sep 02, 14:00, C3.146, Causality Video Club,
Sep 09, 14:00, C3.146, The Logic of Structure-Based Counterfactuals [sections 7.1-7.3 in Causality: Models Reasoning and Inference (2009)] by Judea Pearl, Joris Mooij
Sep 16, 14:00, C3.146, Some Title by Peters Janzing and Schölkopf (2016) [ch. 1], Stephan Bongers
Sep 23, 14:00, C3.146, Some Title by Peters Janzing and Schölkopf (2016) [chs. 2-3], Stephan Bongers
TBA,14:00,C3.146,Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization (2015) by Swaminathan and Joachims,Thorsten Joachims
Nov 4, 14:00, C3.146, Ancestral Graph Markov Models by Richardson and Spirtes (2002) [ch. 1-3], Joris Mooij
Nov 11, 14:00, C3.146, Ancestral Graph Markov Models by Richardson and Spirtes (2002) [ch. 4-6], Tineke Blom
Nov 18, 14:00, C3.146, Ancestral Graph Markov Models by Richardson and Spirtes (2002) [ch. 6–7],Tineke Blom
Nov 25, 14:00, C3.146, Ancestral Graph Markov Models by Richardson and Spirtes (2002) [ch. 8-10], Thijs van Ommen
Dec  16, 14:00, C3.146, Identifying independence in Bayesian Networks by Geiger Verma and Pearl (1990) , Tom Claassen

Older schedules can be found here.