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Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #179
Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi · David Blei · Victor Veitch
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #180
Causal Regularization
Dominik Janzing
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #181
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
Murat Kocaoglu · Amin Jaber · Karthikeyan Shanmugam · Elias Bareinboim
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #182
Debiased Bayesian inference for average treatment effects
Kolyan Ray · Botond Szabo
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #183
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett · Nathan Kallus · Tobias Schnabel
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #184
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets
Daniel Kumor · Bryant Chen · Elias Bareinboim
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #185
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Vasilis Syrgkanis · Victor Lei · Miruna Oprescu · Maggie Hei · Keith Battocchi · Greg Lewis
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #186
Identification of Conditional Causal Effects under Markov Equivalence
Amin Jaber · Jiji Zhang · Elias Bareinboim
Poster
Tue Dec 10th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #187
Variance Reduction in Bipartite Experiments through Correlation Clustering
Jean Pouget-Abadie · Kevin Aydin · Warren Schudy · Kay Brodersen · Vahab Mirrokni
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #134
Identifying Causal Effects via Context-specific Independence Relations
Santtu Tikka · Antti Hyttinen · Juha Karvanen
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #135
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
Robert Ness · Kaushal Paneri · Olga Vitek
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #136
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes
Junzhe Zhang · Elias Bareinboim
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #137
Policy Evaluation with Latent Confounders via Optimal Balance
Andrew Bennett · Nathan Kallus
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #138
Sample Efficient Active Learning of Causal Trees
Kristjan Greenewald · Dmitriy Katz · Karthikeyan Shanmugam · Sara Magliacane · Murat Kocaoglu · Enric Boix Adsera · Guy Bresler
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #139
Selecting causal brain features with a single conditional independence test per feature
Atalanti Mastakouri · Bernhard Schölkopf · Dominik Janzing
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #140
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
Biwei Huang · Kun Zhang · Pengtao Xie · Mingming Gong · Eric Xing · Clark Glymour
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #141
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data
Amanda Gentzel · Dan Garant · David Jensen
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #142
Triad Constraints for Learning Causal Structure of Latent Variables
Ruichu Cai · Feng Xie · Clark Glymour · Zhifeng Hao · Kun Zhang
Poster
Tue Dec 10th 05:30 -- 07:30 PM @ East Exhibition Hall B + C #143
Using Embeddings to Correct for Unobserved Confounding in Networks
Victor Veitch · Yixin Wang · David Blei