Alexis Bellot

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 35

Top Topics

Hierarchical Bayesian Model

Conditional Independence

Markov Property

Causal Discovery

Top Venues

Publications

Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
Mind the Graph When Balancing Data for Fairness or Robustness. CoRR (2024)
Alexis Bellot, Mihaela van der Schaar
Linear Deconfounded Score Method: Scoring DAGs With Dense Unobserved Confounding. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. CoRR (2024)
Alexis Bellot, Junzhe Zhang, Elias Bareinboim
Scores for Learning Discrete Causal Graphs with Unobserved Confounders. AAAI (2024)
Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
Functional causal Bayesian optimization. UAI (2023)
Alexis Bellot, Alan Malek, Silvia Chiappa
Transportability for Bandits with Data from Different Environments. NeurIPS (2023)
Alexis Bellot
Towards Bounding Causal Effects under Markov Equivalence. CoRR (2023)
Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program (2023)
Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
Functional Causal Bayesian Optimization. CoRR (2023)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. CoRR (2022)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. ICML (2022)
Alexis Bellot, Kim Branson, Mihaela van der Schaar
Neural graphical modelling in continuous-time: consistency guarantees and algorithms. ICLR (2022)
Alexis Bellot, Anish Dhir, Giulia Prando
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage. CoRR (2022)
Alexis Bellot, Mihaela van der Schaar
A kernel two-sample test with selection bias. UAI (2021)
Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms. CoRR (2021)
Alexis Bellot, Mihaela van der Schaar
Policy Analysis using Synthetic Controls in Continuous-Time. ICML (2021)
Alexis Bellot, Mihaela van der Schaar
Policy Analysis using Synthetic Controls in Continuous-Time. CoRR (2021)
Alexis Bellot, Mihaela van der Schaar
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding. CoRR (2021)
Alexis Bellot, Mihaela van der Schaar
Application of kernel hypothesis testing on set-valued data. UAI (2021)
Alexis Bellot, Kim Branson, Mihaela van der Schaar
Consistency of mechanistic causal discovery in continuous-time using Neural ODEs. CoRR (2021)
Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms. NeurIPS (2021)
Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. AISTATS (2020)
Alexis Bellot, Mihaela van der Schaar
Generalization and Invariances in the Presence of Unobserved Confounding. CoRR (2020)
Yao Zhang, Alexis Bellot, Mihaela van der Schaar
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects. AISTATS (2020)
Yao Zhang, Alexis Bellot, Mihaela van der Schaar
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects. CoRR (2020)
Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Jem Rashbass, Mihaela van der Schaar
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. CoRR (2020)
Alexis Bellot, Mihaela van der Schaar
Flexible Modelling of Longitudinal Medical Data: A Bayesian Nonparametric Approach. ACM Trans. Comput. Heal. 1 (1) (2020)
Alexis Bellot, Mihaela van der Schaar
A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records. CoRR (2019)
Alexis Bellot, Mihaela van der Schaar
Boosting Transfer Learning with Survival Data from Heterogeneous Domains. AISTATS (2019)
Alexis Bellot, Mihaela van der Schaar
Conditional Independence Testing using Generative Adversarial Networks. NeurIPS (2019)
Alexis Bellot, Mihaela van der Schaar
Conditional Independence Testing using Generative Adversarial Networks. CoRR (2019)
Alexis Bellot, Mihaela van der Schaar
A Hierarchical Bayesian Model for Personalized Survival Predictions. IEEE J. Biomed. Health Informatics 23 (1) (2019)
Alexis Bellot, Mihaela van der Schaar
Boosted Trees for Risk Prognosis. MLHC (2018)
Alexis Bellot, Mihaela van der Schaar
Tree-based Bayesian Mixture Model for Competing Risks. AISTATS (2018)
Alexis Bellot, Mihaela van der Schaar
Multitask Boosting for Survival Analysis with Competing Risks. NeurIPS (2018)