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07/05/2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
We tackle the problems of latent variables identification and "out-of-su...
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11/26/2022
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective
Although disentangled representations are often said to be beneficial fo...
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11/03/2022
Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation
We study the problem of model selection in causal inference, specificall...
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04/10/2022
Towards efficient representation identification in supervised learning
Humans have a remarkable ability to disentangle complex sensory inputs (...
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10/07/2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
With the goal of generalizing to out-of-distribution (OOD) data, recent ...
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11/11/2020
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
For many kinds of interventions, such as a new advertisement, marketing ...
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11/10/2020
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
To explain a machine learning model, there are two main approaches: feat...
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06/12/2020
Domain Generalization using Causal Matching
Learning invariant representations has been proposed as a key technique ...
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12/06/2019
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
Explaining the output of a complex machine learning (ML) model often req...
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06/07/2019