Bellot, Alexis

23 publications

ICML 2025 FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa

ICML 2025 The Limits of Predicting Agents from Behaviour Alexis Bellot, Jonathan Richens, Tom Everitt

NeurIPS 2024 Efficient Policy Evaluation Across Multiple Different Experimental Datasets Yonghan Jung, Alexis Bellot

NeurIPS 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

NeurIPS 2024 Partial Transportability for Domain Generalization Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim

AAAI 2024 Scores for Learning Discrete Causal Graphs with Unobserved Confounders Alexis Bellot, Junzhe Zhang, Elias Bareinboim

UAI 2024 Towards Bounding Causal Effects Under Markov Equivalence Alexis Bellot

NeurIPS 2024 Towards Estimating Bounds on the Effect of Policies Under Unobserved Confounding Alexis Bellot, Silvia Chiappa

UAI 2023 Functional Causal Bayesian Optimization Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa

NeurIPS 2023 Transportability for Bandits with Data from Different Environments Alexis Bellot, Alan Malek, Silvia Chiappa

ICML 2022 Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela Schaar

ICLR 2022 Neural Graphical Modelling in Continuous-Time: Consistency Guarantees and Algorithms Alexis Bellot, Kim Branson, Mihaela van der Schaar

UAI 2021 A Kernel Two-Sample Test with Selection Bias Alexis Bellot, Mihaela Schaar

UAI 2021 Application of Kernel Hypothesis Testing on Set-Valued Data Alexis Bellot, Mihaela Schaar

NeurIPS 2021 MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar

ICML 2021 Policy Analysis Using Synthetic Controls in Continuous-Time Alexis Bellot, Mihaela Schaar

AISTATS 2020 Learning Dynamic and Personalized Comorbidity Networks from Event Data Using Deep Diffusion Processes Zhaozhi Qian, Ahmed Alaa, Alexis Bellot, Mihaela Schaar, Jem Rashbass

AISTATS 2020 Learning Overlapping Representations for the Estimation of Individualized Treatment Effects Yao Zhang, Alexis Bellot, Mihaela Schaar

AISTATS 2019 Boosting Transfer Learning with Survival Data from Heterogeneous Domains Alexis Bellot, Mihaela Schaar

NeurIPS 2019 Conditional Independence Testing Using Generative Adversarial Networks Alexis Bellot, Mihaela van der Schaar

MLHC 2018 Boosted Trees for Risk Prognosis Alexis Bellot, Mihaela van der Schaar

NeurIPS 2018 Multitask Boosting for Survival Analysis with Competing Risks Alexis Bellot, Mihaela van der Schaar

AISTATS 2018 Tree-Based Bayesian Mixture Model for Competing Risks Alexis Bellot, Mihaela van der Schaar