Robin J. Evans

According to our database, Robin J. Evans authored at least 18 papers between 2010 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Testing Generalizability in Causal Inference.

Daniel de Vassimon Manela, Linying Yang, Robin J. Evans

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

2024

Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects.

Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic

Trans. Mach. Learn. Res., 2024

Toward a Complete Criterion for Value of Information in Insoluble Decision Problems.

Ryan Carey, Sanghack Lee, Robin J. Evans

Trans. Mach. Learn. Res., 2024

A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment.

Robert Hu, Dino Sejdinovic, Robin J. Evans

J. Mach. Learn. Res., 2024

A fast score-based search algorithm for maximal ancestral graphs using entropy.

Zhongyi Hu, Robin Evans

CoRR, 2024

Marginal Causal Flows for Validation and Inference.

Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Results on Counterfactual Invariance.

Jake Fawkes, Robin J. Evans

CoRR, 2023

PWSHAP: A Path-Wise Explanation Model for Targeted Variables.

Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes

Proceedings of the International Conference on Machine Learning, 2023

2022

Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Even Under One Sided Overlap.

Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic

CoRR, 2022

Selection, Ignorability and Challenges With Causal Fairness.

Jake Fawkes, Robin J. Evans, Dino Sejdinovic

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Dependency in DAG models with hidden variables.

Robin J. Evans

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Faster algorithms for Markov equivalence.

Zhongyi Hu, Robin Evans

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2018

Acyclic Linear SEMs Obey the Nested Markov Property.

Ilya Shpitser, Robin J. Evans, Thomas S. Richardson

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2016

Causal Inference through a Witness Protection Program.

Ricardo Silva, Robin J. Evans

J. Mach. Learn. Res., 2016

One-component regular variation and graphical modeling of extremes.

Adrien Hitz, Robin Evans

J. Appl. Probab., 2016

2015

Recovering from Selection Bias using Marginal Structure in Discrete Models.

Robin J. Evans, Vanessa Didelez

Proceedings of the UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 2015

2013

Sparse Nested Markov models with Log-linear Parameters.

Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2010

Maximum likelihood fitting of acyclic directed mixed graphs to binary data.

Robin J. Evans, Thomas S. Richardson

Proceedings of the UAI 2010, 2010