Alexis Bellot - RankMe

47 papers A* 14A 8Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Evaluating the Goal-Directedness of Large Language Models. CoRR Tom Everitt, Cristina Garbacea, Alexis Bellot, Jonathan Richens, Henry Papadatos, Siméon Campos, Rohin Shah
2025	A*	`conf`	FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. ICML Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
2025	J	`jnl`	General agents need world models. CoRR Jonathan Richens, David Abel, Alexis Bellot, Tom Everitt
2025	J	`jnl`	Partial Transportability for Domain Generalization. CoRR Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim
2025	A*	`conf`	The Limits of Predicting Agents from Behaviour. ICML Alexis Bellot, Jonathan Richens, Tom Everitt
2025	J	`jnl`	The Limits of Predicting Agents from Behaviour. CoRR Alexis Bellot, Jonathan Richens, Tom Everitt
2024	A*	`conf`	Efficient Policy Evaluation Across Multiple Different Experimental Datasets. NeurIPS Yonghan Jung, Alexis Bellot
2024	J	`jnl`	FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. CoRR Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
2024	J	`jnl`	Linear Deconfounded Score Method: Scoring DAGs With Dense Unobserved Confounding. IEEE Trans. Neural Networks Learn. Syst. Alexis Bellot, Mihaela van der Schaar
2024	A*	`conf`	Mind the Graph When Balancing Data for Fairness or Robustness. NeurIPS Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
2024	J	`jnl`	Mind the Graph When Balancing Data for Fairness or Robustness. CoRR Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
2024	A*	`conf`	Partial Transportability for Domain Generalization. NeurIPS Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim
2024	A*	`conf`	Scores for Learning Discrete Causal Graphs with Unobserved Confounders. AAAI Alexis Bellot, Junzhe Zhang, Elias Bareinboim
2024	A	`conf`	Towards Bounding Causal Effects under Markov Equivalence. UAI Alexis Bellot
2024	A*	`conf`	Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding. NeurIPS Alexis Bellot, Silvia Chiappa
2023	—	`ed.`	AAAI Bridge Program on Continual Causality, 7-8 February 2023, Washington, DC, USA AAAI Bridge Program Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
2023	—	`conf`	Continual Causality: A Retrospective of the Inaugural AAAI-23 Bridge Program. AAAI Bridge Program Martin Mundt, Keiland W. Cooper, Devendra Singh Dhami, Adèle H. Ribeiro, James Seale Smith, Alexis Bellot, Tyler L. Hayes
2023	J	`jnl`	Functional Causal Bayesian Optimization. CoRR Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
2023	A	`conf`	Functional causal Bayesian optimization. UAI Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
2023	J	`jnl`	Towards Bounding Causal Effects under Markov Equivalence. CoRR Alexis Bellot
2023	A*	`conf`	Transportability for Bandits with Data from Different Environments. NeurIPS Alexis Bellot, Alan Malek, Silvia Chiappa
2022	A*	`conf`	Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. ICML Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
2022	J	`jnl`	Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. CoRR Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
2022	J	`jnl`	Generalization bounds and algorithms for estimating conditional average treatment effect of dosage. CoRR Alexis Bellot, Anish Dhir, Giulia Prando
2022	A*	`conf`	Neural graphical modelling in continuous-time: consistency guarantees and algorithms. ICLR Alexis Bellot, Kim Branson, Mihaela van der Schaar
2021	A	`conf`	A kernel two-sample test with selection bias. UAI Alexis Bellot, Mihaela van der Schaar
2021	A	`conf`	Application of kernel hypothesis testing on set-valued data. UAI Alexis Bellot, Mihaela van der Schaar
2021	J	`jnl`	Consistency of mechanistic causal discovery in continuous-time using Neural ODEs. CoRR Alexis Bellot, Kim Branson, Mihaela van der Schaar
2021	J	`jnl`	Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding. CoRR Alexis Bellot, Mihaela van der Schaar
2021	A*	`conf`	MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms. NeurIPS Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar
2021	J	`jnl`	MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms. CoRR Trent Kyono, Yao Zhang, Alexis Bellot, Mihaela van der Schaar
2021	A*	`conf`	Policy Analysis using Synthetic Controls in Continuous-Time. ICML Alexis Bellot, Mihaela van der Schaar
2021	J	`jnl`	Policy Analysis using Synthetic Controls in Continuous-Time. CoRR Alexis Bellot, Mihaela van der Schaar
2020	J	`jnl`	Flexible Modelling of Longitudinal Medical Data: A Bayesian Nonparametric Approach. ACM Trans. Comput. Heal. Alexis Bellot, Mihaela van der Schaar
2020	J	`jnl`	Generalization and Invariances in the Presence of Unobserved Confounding. CoRR Alexis Bellot, Mihaela van der Schaar
2020	A	`conf`	Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. AISTATS Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass
2020	J	`jnl`	Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. CoRR Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Jem Rashbass, Mihaela van der Schaar
2020	A	`conf`	Learning Overlapping Representations for the Estimation of Individualized Treatment Effects. AISTATS Yao Zhang, Alexis Bellot, Mihaela van der Schaar
2020	J	`jnl`	Learning Overlapping Representations for the Estimation of Individualized Treatment Effects. CoRR Yao Zhang, Alexis Bellot, Mihaela van der Schaar
2019	J	`jnl`	A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records. CoRR Alexis Bellot, Mihaela van der Schaar
2019	J	`jnl`	A Hierarchical Bayesian Model for Personalized Survival Predictions. IEEE J. Biomed. Health Informatics Alexis Bellot, Mihaela van der Schaar
2019	A	`conf`	Boosting Transfer Learning with Survival Data from Heterogeneous Domains. AISTATS Alexis Bellot, Mihaela van der Schaar
2019	A*	`conf`	Conditional Independence Testing using Generative Adversarial Networks. NeurIPS Alexis Bellot, Mihaela van der Schaar
2019	J	`jnl`	Conditional Independence Testing using Generative Adversarial Networks. CoRR Alexis Bellot, Mihaela van der Schaar
2018	—	`conf`	Boosted Trees for Risk Prognosis. MLHC Alexis Bellot, Mihaela van der Schaar
2018	A*	`conf`	Multitask Boosting for Survival Analysis with Competing Risks. NeurIPS Alexis Bellot, Mihaela van der Schaar
2018	A	`conf`	Tree-based Bayesian Mixture Model for Competing Risks. AISTATS Alexis Bellot, Mihaela van der Schaar