Papers
Variance reduction combining pre-experiment and in-experiment data
Zhexiao Lin, Pablo Crespo
Estimating Joint Interventional Distributions from Marginal Interventional Data
Sergio Hernan Garrido Mejia, Elke Kirschbaum, Armin Kekić et al.
Learning and Testing Exposure Mappings of Interference using Graph Convolutional Autoencoders
Martin Huber, Jannis Kueck, Mara Mattes
Causal Importance for Physics-Informed Machine Learning
Daniel Fiifi Tawia Hagan, Thomas Mortier, Cas Decancq et al.
Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
Katherine Avery, Chinmay Pendse, David Jensen
Learning a Spatial Partitioning and its Causal Relations from Temporal Data
Philippe Brouillard, Sebastien Lachapelle, Julia Kaltenborn et al.
Improving Generative Methods for Causal Evaluation via Simulation-Based Inference
Pracheta Amaranath, Vinitra Muralikrishnan, Amit Sharma et al.
Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases
Federico Baldo, Simon Ferreira, Charles K. Assaad
Automatic debiased machine learning and sensitivity analysis for sample selection models
Jakob Bjelac, Victor Chernozhukov, Phil-Adrian Klotz et al.
Bayesian Hierarchical Invariant Prediction
Francisco Madaleno, Pernille Julie Viuff Sand, Francisco C. Pereira et al.
DAG Learning from Zero-Inflated Count Data Using Continuous Optimization
Noriaki Sato, Marco Scutari, Shuichi Kawano et al.
Causal-ICM: A Data Fusion Framework For Heterogeneous Treatment Effect Estimation With Multi-Task Gaussian Processes
Evangelos Dimitriou, Edwin Fong, Jens Magelund Tarp et al.
Valid Inference for Treatment Effects under Multimodal Confounding
Martin Spindler, Philipp Bach, Victor Chernozhukov et al.
Understanding Task Representations in Neural Networks via Bayesian Ablation
Andrew Joohun Nam, Declan Iain Campbell, Thomas L. Griffiths et al.
A fine-grained look at causal effects in causal spaces
Junhyung Park, Yuqing Zhou
Disentangling Dynamical Systems: Causal Representation Learning Meets Local Sparse Attention
Markus W. Baumgartner, Anson Lei, Joe Watson et al.
Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects
Timothée Loranchet, Charles K. Assaad
Consistent End-to-End Estimation for Counterfactual Fairness
Yuchen Ma, Valentyn Melnychuk, Dennis Frauen et al.
Efficient and Provable Algorithms for Covariate Shift
Deeksha Adil, Jaroslaw Blasiok
Convex optimization with p-norm oracles
Deeksha Adil, Brian Bullins, Arun Jambulapati et al.
Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
Shubhada Agrawal, Aaditya Ramdas
Learning from Synthetic Data: Limitations of ERM
Kareem Amin, Alex Bie, Weiwei Kong et al.