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07/31/2023
Approximating Counterfactual Bounds while Fusing Observational, Biased and Randomised Data Sources
We address the problem of integrating data from multiple, possibly biase...
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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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12/06/2022
Learning to Bound Counterfactual Inference in Structural Causal Models from Observational and Randomised Data
We address the problem of integrating data from multiple observational a...
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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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10/26/2021
Diversity and Generalization in Neural Network Ensembles
Ensembles are widely used in machine learning and, usually, provide stat...
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05/10/2021
CREPO: An Open Repository to Benchmark Credal Network Algorithms
Credal networks are a popular class of imprecise probabilistic graphical...
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11/04/2020
EM Based Bounding of Unidentifiable Queries in Structural Causal Models
A structural causal model is made of endogenous (manifest) and exogenous...
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08/02/2020
Structural Causal Models Are (Solvable by) Credal Networks
A structural causal model is made of endogenous (manifest) and exogenous...
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08/29/2019
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy
InferPy is a Python package for probabilistic modeling with deep neural ...
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08/09/2019
Probabilistic Models with Deep Neural Networks
Recent advances in statistical inference have significantly expanded the...
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04/04/2017
