Virginia Aglietti

According to our database, Virginia Aglietti authored at least 13 papers between 2018 and 2024.

Collaborative distances:

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

2024

GradINN: Gradient Informed Neural Network.

Filippo Aglietti, Francesco Della Santa, Andrea Piano, Virginia Aglietti

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

2023

Functional causal Bayesian optimization.

Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Additive Causal Bandits with Unknown Graph.

Alan Malek, Virginia Aglietti, Silvia Chiappa

Proceedings of the International Conference on Machine Learning, 2023

Constrained Causal Bayesian Optimization.

Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa

Proceedings of the International Conference on Machine Learning, 2023

Causal Entropy Optimization.

Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities.

Shanaka Perera, Virginia Aglietti, Theodoros Damoulas

CoRR, 2021

Dynamic Causal Bayesian Optimization.

Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

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

2020

Multi-task Causal Learning with Gaussian Processes.

Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Causal Bayesian Optimization.

Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González

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

2019

Structured Variational Inference in Continuous Cox Process Models.

Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps

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

Efficient Inference in Multi-task Cox Process Models.

Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla

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

2018

Log Gaussian Cox Process Networks.

Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla

CoRR, 2018