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ORCIDCiarán M. Gilligan-Lee
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2020 – today
- 2024
[j2]Ciarán M. Gilligan-Lee
, Christopher Hart, Jonathan G. Richens, Saurabh Johri:
Leveraging Directed Causal Discovery to Detect Latent Common Causes in Cause-Effect Pairs. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4938-4947 (2024)- 2023
- [j1]Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee:
Estimating categorical counterfactuals via deep twin networks. Nat. Mac. Intell. 5(2): 159-168 (2023) - [c4]Graham Van Goffrier, Lucas Maystre, Ciarán Mark Gilligan-Lee:
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding. CLeaR 2023: 791-813 - [c3]Jakob Zeitler, Athanasios Vlontzos, Ciarán Mark Gilligan-Lee:
Non-parametric identifiability and sensitivity analysis of synthetic control models. CLeaR 2023: 850-865 - [i6]Jakob Zeitler, Athanasios Vlontzos, Ciarán M. Gilligan-Lee:
Non-parametric identifiability and sensitivity analysis of synthetic control models. CoRR abs/2301.07656 (2023) - [i5]Graham Van Goffrier, Lucas Maystre, Ciarán M. Gilligan-Lee:
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding. CoRR abs/2302.10625 (2023) - 2022
- [c2]Hadrien Reynaud, Athanasios Vlontzos, Mischa Dombrowski, Ciarán M. Gilligan-Lee, Arian Beqiri, Paul Leeson, Bernhard Kainz:
D'ARTAGNAN: Counterfactual Video Generation. MICCAI (8) 2022: 599-609 - [c1]Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas:
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. NeurIPS 2022 - [i4]Hadrien Reynaud, Athanasios Vlontzos, Mischa Dombrowski, Ciarán M. Gilligan-Lee, Arian Beqiri, Paul Leeson, Bernhard Kainz:
D'ARTAGNAN: Counterfactual Video Generation. CoRR abs/2206.01651 (2022) - [i3]Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas:
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. CoRR abs/2210.05446 (2022) - 2021
- [i2]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:
Technology Readiness Levels for Machine Learning Systems. CoRR abs/2101.03989 (2021) - [i1]Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee:
Estimating the probabilities of causation via deep monotonic twin networks. CoRR abs/2109.01904 (2021)
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