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07/17/2023
Efficient Computation of Counterfactual Bounds
We assume to be given structural equations over discrete variables induc...
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02/01/2023
Learning Choice Functions with Gaussian Processes
In consumer theory, ranking available objects by means of preference rel...
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10/05/2022
Probabilistic reconciliation of forecasts via importance sampling
Hierarchical time series are common in several applied fields. Forecasts...
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07/26/2022
Bounding Counterfactuals under Selection Bias
Causal analysis may be affected by selection bias, which is defined as t...
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07/19/2022
Probabilistic Reconciliation of Count Time Series
We propose a principled method for the reconciliation of any probabilist...
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12/17/2021
Correlated Product of Experts for Sparse Gaussian Process Regression
Gaussian processes (GPs) are an important tool in machine learning and s...
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10/15/2021
Choice functions based multi-objective Bayesian optimisation
In this work we introduce a new framework for multi-objective Bayesian o...
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12/12/2020
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes
Skew-Gaussian processes (SkewGPs) extend the multivariate Unified Skew-N...
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11/13/2020
An exact kernel framework for spatio-temporal dynamics
A kernel-based framework for spatio-temporal data analysis is introduced...
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08/15/2020
Preferential Bayesian optimisation with Skew Gaussian Processes
Bayesian optimisation (BO) is a very effective approach for sequential b...
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07/13/2020
Orthogonally Decoupled Variational Fourier Features
Sparse inducing points have long been a standard method to fit Gaussian ...
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05/26/2020
Skew Gaussian Processes for Classification
Gaussian processes (GPs) are distributions over functions, which provide...
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06/07/2019
Reconciling Hierarchical Forecasts via Bayes' Rule
When time series are organized into hierarchies, the forecasts have to s...
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05/28/2019
Recursive Estimation for Sparse Gaussian Process Regression
Gaussian Processes (GPs) are powerful kernelized methods for non-paramet...
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01/15/2015