Alexis Bellot

According to our database, Alexis Bellot authored at least 28 papers between 2018 and 2024.

Collaborative distances:

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

2024

Linear Deconfounded Score Method: Scoring DAGs With Dense Unobserved Confounding.

Alexis Bellot, Mihaela van der Schaar

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

Mind the Graph When Balancing Data for Fairness or Robustness.

Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa

CoRR, 2024

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch.

Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa

CoRR, 2024

Scores for Learning Discrete Causal Graphs with Unobserved Confounders.

Alexis Bellot, Junzhe Zhang, Elias Bareinboim

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Towards Bounding Causal Effects under Markov Equivalence.

Alexis Bellot

CoRR, 2023

Functional causal Bayesian optimization.

Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Transportability for Bandits with Data from Different Environments.

Alexis Bellot, Alan Malek, Silvia Chiappa

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program.

Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Generalization bounds and algorithms for estimating conditional average treatment effect of dosage.

Alexis Bellot, Anish Dhir, Giulia Prando

CoRR, 2022

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations.

Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar

Proceedings of the International Conference on Machine Learning, 2022

Neural graphical modelling in continuous-time: consistency guarantees and algorithms.

Alexis Bellot, Kim Branson, Mihaela van der Schaar

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Consistency of mechanistic causal discovery in continuous-time using Neural ODEs.

Alexis Bellot, Kim Branson, Mihaela van der Schaar

CoRR, 2021

Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding.

Alexis Bellot, Mihaela van der Schaar

CoRR, 2021

A kernel two-sample test with selection bias.

Alexis Bellot, Mihaela van der Schaar

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

Application of kernel hypothesis testing on set-valued data.

Alexis Bellot, Mihaela van der Schaar

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

MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms.

Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Policy Analysis using Synthetic Controls in Continuous-Time.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Flexible Modelling of Longitudinal Medical Data: A Bayesian Nonparametric Approach.

Alexis Bellot, Mihaela van der Schaar

ACM Trans. Comput. Heal., 2020

Generalization and Invariances in the Presence of Unobserved Confounding.

Alexis Bellot, Mihaela van der Schaar

CoRR, 2020

Learning Overlapping Representations for the Estimation of Individualized Treatment Effects.

Yao Zhang, Alexis Bellot, Mihaela van der Schaar

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes.

Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

A Hierarchical Bayesian Model for Personalized Survival Predictions.

Alexis Bellot, Mihaela van der Schaar

IEEE J. Biomed. Health Informatics, 2019

A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records.

Alexis Bellot, Mihaela van der Schaar

CoRR, 2019

Conditional Independence Testing using Generative Adversarial Networks.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Boosting Transfer Learning with Survival Data from Heterogeneous Domains.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Multitask Boosting for Survival Analysis with Competing Risks.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Boosted Trees for Risk Prognosis.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the Machine Learning for Healthcare Conference, 2018

Tree-based Bayesian Mixture Model for Competing Risks.

Alexis Bellot, Mihaela van der Schaar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018