Robin J. Evans

24 papers A* 2A 6Journal 12Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A conf
Testing Generalizability in Causal Inference.
UAI
Daniel de Vassimon Manela, Linying Yang, Robin J. Evans
2024 J jnl
A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment.
J. Mach. Learn. Res.
Robert Hu, Dino Sejdinovic, Robin J. Evans
2024 J jnl
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects.
Trans. Mach. Learn. Res.
Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic
2024 A* conf
Marginal Causal Flows for Validation and Inference.
NeurIPS
Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans
2024 J jnl
Marginal Causal Flows for Validation and Inference.
CoRR
Daniel de Vassimon Manela, Laura Battaglia, Robin J. Evans
2024 J jnl
Testing Generalizability in Causal Inference.
CoRR
Daniel de Vassimon Manela, Linying Yang, Robin J. Evans
2024 J jnl
Toward a Complete Criterion for Value of Information in Insoluble Decision Problems.
Trans. Mach. Learn. Res.
Ryan Carey, Sanghack Lee, Robin J. Evans
2023 A* conf
PWSHAP: A Path-Wise Explanation Model for Targeted Variables.
ICML
Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes
2023 J jnl
PWSHAP: A Path-Wise Explanation Model for Targeted Variables.
CoRR
Lucile Ter-Minassian, Oscar Clivio, Karla Diaz-Ordaz, Robin J. Evans, Chris C. Holmes
2023 J jnl
Results on Counterfactual Invariance.
CoRR
Jake Fawkes, Robin J. Evans
2023 A ed.
Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA.
UAI
Robin J. Evans, Ilya Shpitser
2022 J jnl
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Even Under One Sided Overlap.
CoRR
Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic
2022 — conf
Selection, Ignorability and Challenges With Causal Fairness.
CLeaR
Jake Fawkes, Robin J. Evans, Dino Sejdinovic
2022 J jnl
Selection, Ignorability and Challenges With Causal Fairness.
CoRR
Jake Fawkes, Robin J. Evans, Dino Sejdinovic
2021 A conf
Dependency in DAG models with hidden variables.
UAI
Robin J. Evans
2018 A conf
Acyclic Linear SEMs Obey the Nested Markov Property.
UAI
Ilya Shpitser, Robin J. Evans, Thomas S. Richardson
2016 J jnl
Causal Inference through a Witness Protection Program.
J. Mach. Learn. Res.
Ricardo Silva, Robin J. Evans
2015 — ed.
Proceedings of the UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, The Netherlands, July 16, 2015.
ACI@UAI
Ricardo Silva, Ilya Shpitser, Robin J. Evans, Jonas Peters, Tom Claassen
2015 — conf
Recovering from Selection Bias using Marginal Structure in Discrete Models.
ACI@UAI
Robin J. Evans, Vanessa Didelez
2014 — conf
Causal Inference through a Witness Protection Program.
NIPS
Ricardo Silva, Robin J. Evans
2013 A conf
Sparse Nested Markov models with Log-linear Parameters.
UAI
Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins
2013 J jnl
Sparse Nested Markov models with Log-linear Parameters.
CoRR
Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins
2012 J jnl
Maximum likelihood fitting of acyclic directed mixed graphs to binary data
CoRR
Robin J. Evans, Thomas S. Richardson
2010 A conf
Maximum likelihood fitting of acyclic directed mixed graphs to binary data.
UAI
Robin J. Evans, Thomas S. Richardson