Ciarán M. Gilligan-Lee

According to our database, Ciarán M. Gilligan-Lee authored at least 10 papers between 2021 and 2024.

Collaborative distances:

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

2024

Leveraging Directed Causal Discovery to Detect Latent Common Causes in Cause-Effect Pairs.

Ciarán M. Gilligan-Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Nature versus nurture in galaxy formation: the effect of environment on star formation with causal machine learning.

Sunil Mucesh, William G. Hartley, Ciarán M. Gilligan-Lee, Ofer Lahav

CoRR, 2024

Contrastive representations of high-dimensional, structured treatments.

Oriol Corcoll Andreu, Athanasios Vlontzos, Michael O'Riordan, Ciarán M. Gilligan-Lee

CoRR, 2024

2023

Estimating categorical counterfactuals via deep twin networks.

Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee

Nat. Mac. Intell., February, 2023

Non-parametric identifiability and sensitivity analysis of synthetic control models.

Jakob Zeitler, Athanasios Vlontzos, Ciarán Mark Gilligan-Lee

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding.

Graham W. Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders.

Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

D'ARTAGNAN: Counterfactual Video Generation.

Hadrien Reynaud, Athanasios Vlontzos, Mischa Dombrowski, Ciarán M. Gilligan-Lee, Arian Beqiri, Paul Leeson, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Estimating the probabilities of causation via deep monotonic twin networks.

Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee

CoRR, 2021

Technology Readiness Levels for Machine Learning Systems.

Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr

CoRR, 2021