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Virginia Aglietti
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2020 – today
- 2024
- [i13]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 abs/2406.04824 (2024) - [i12]Filippo Aglietti, Francesco Della Santa, Andrea Piano, Virginia Aglietti:
GradINN: Gradient Informed Neural Network. CoRR abs/2409.01914 (2024) - [i11]Eleni Sgouritsa, Virginia Aglietti, Yee Whye Teh, Arnaud Doucet, Arthur Gretton, Silvia Chiappa:
Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation. CoRR abs/2412.13952 (2024) - 2023
- [c9]Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas:
Causal Entropy Optimization. AISTATS 2023: 8586-8605 - [c8]Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa:
Constrained Causal Bayesian Optimization. ICML 2023: 304-321 - [c7]Alan Malek, Virginia Aglietti, Silvia Chiappa:
Additive Causal Bandits with Unknown Graph. ICML 2023: 23574-23589 - [c6]Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa:
Functional causal Bayesian optimization. UAI 2023: 756-765 - [i10]Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa:
Constrained Causal Bayesian Optimization. CoRR abs/2305.20011 (2023) - [i9]Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa:
Functional Causal Bayesian Optimization. CoRR abs/2306.06409 (2023) - [i8]Alan Malek, Virginia Aglietti, Silvia Chiappa:
Additive Causal Bandits with Unknown Graph. CoRR abs/2306.07858 (2023) - 2022
- [i7]Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas:
Causal Entropy Optimization. CoRR abs/2208.10981 (2022) - 2021
- [c5]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. NeurIPS 2021: 10549-10560 - [i6]Shanaka Perera, Virginia Aglietti, Theodoros Damoulas:
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities. CoRR abs/2108.02594 (2021) - [i5]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. CoRR abs/2110.13891 (2021) - 2020
- [c4]Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González:
Causal Bayesian Optimization. AISTATS 2020: 3155-3164 - [c3]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. NeurIPS 2020 - [i4]Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González:
Causal Bayesian Optimization. CoRR abs/2005.11741 (2020) - [i3]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. CoRR abs/2009.12821 (2020)
2010 – 2019
- 2019
- [c2]Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla:
Efficient Inference in Multi-task Cox Process Models. AISTATS 2019: 537-546 - [c1]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. NeurIPS 2019: 12437-12447 - [i2]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. CoRR abs/1906.03161 (2019) - 2018
- [i1]Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla:
Log Gaussian Cox Process Networks. CoRR abs/1805.09781 (2018)
Coauthor Index

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