Dario Azzimonti

Orcid: 0000-0001-5080-3061

According to our database1, Dario Azzimonti authored at least 23 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Efficient probabilistic reconciliation of forecasts for real-valued and count time series.
Stat. Comput., February, 2024

Efficient computation of counterfactual bounds.
Int. J. Approx. Reason., 2024

A tutorial on learning from preferences and choices with Gaussian Processes.
CoRR, 2024

2023
Correlated product of experts for sparse Gaussian process regression.
Mach. Learn., May, 2023

Learning Choice Functions with Gaussian Processes.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Bayesian Optimization For Choice Data.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022
Probabilistic reconciliation of forecasts via importance sampling.
CoRR, 2022

Bounding Counterfactuals under Selection Bias.
Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2021
Adaptive Design of Experiments for Conservative Estimation of Excursion Sets.
Technometrics, 2021

A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes.
Mach. Learn., 2021

Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets [Invited].
JOCN, 2021

Choice functions based multi-objective Bayesian optimisation.
CoRR, 2021

Sparse Information Filter for Fast Gaussian Process Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Preferential Bayesian optimisation with skew gaussian processes.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020
Skew Gaussian processes for classification.
Mach. Learn., 2020

Reducing probes for quality of transmission estimation in optical networks with active learning.
JOCN, 2020

Orthogonally Decoupled Variational Fourier Features.
CoRR, 2020

Recursive estimation for sparse Gaussian process regression.
Autom., 2020

Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Active vs Transfer Learning Approaches for QoT Estimation with Small Training Datasets.
Proceedings of the Optical Fiber Communications Conference and Exhibition, 2020

2019
Profile Extrema for Visualizing and Quantifying Uncertainties on Excursion Regions: Application to Coastal Flooding.
Technometrics, 2019

Using Active Learning to Decrease Probes for QoT Estimation in Optical Networks.
Proceedings of the Optical Fiber Communications Conference and Exhibition, 2019

2016
Quantifying Uncertainties on Excursion Sets Under a Gaussian Random Field Prior.
SIAM/ASA J. Uncertain. Quantification, 2016


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