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06/08/2023
Causal normalizing flows: from theory to practice
In this work, we deepen on the use of normalizing flows for causal reaso...
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02/13/2023
Variational Mixture of HyperGenerators for Learning Distributions Over Functions
Recent approaches build on implicit neural representations (INRs) to pro...
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11/21/2022
Learnable Graph Convolutional Attention Networks
Existing Graph Neural Networks (GNNs) compute the message exchange betwe...
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06/09/2022
Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization
A number of variational autoencoders (VAEs) have recently emerged with t...
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05/10/2022
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making
Decision making algorithms, in practice, are often trained on data that ...
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10/27/2021
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries
In this paper, we introduce VACA, a novel class of variational graph aut...
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03/03/2021
Rotograd: Dynamic Gradient Homogenization for Multi-Task Learning
While multi-task learning (MTL) has been successfully applied in several...
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02/08/2021
A Ranking Approach to Fair Classification
Algorithmic decision systems are increasingly used in areas such as hiri...
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10/13/2020
On the Fairness of Causal Algorithmic Recourse
While many recent works have studied the problem of algorithmic fairness...
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10/10/2020
Scaling Guarantees for Nearest Counterfactual Explanations
Counterfactual explanations (CFE) are being widely used to explain algor...
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10/08/2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Machine learning is increasingly used to inform decision-making in sensi...
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06/11/2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Recent work has discussed the limitations of counterfactual explanations...
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02/26/2020
Lipschitz standardization for robust multivariate learning
Current trends in machine learning rely on out-of-the-box gradient-based...
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02/14/2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions
As machine learning is increasingly used to inform consequential decisio...
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05/27/2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions
Predictive models are being increasingly used to support consequential d...
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02/08/2019
Improving Consequential Decision Making under Imperfect Predictions
Consequential decisions are increasingly informed by sophisticated data-...
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10/18/2018
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation
New communication standards need to deal with machine-to-machine communi...
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07/24/2018
Automatic Bayesian Density Analysis
Making sense of a dataset in an automatic and unsupervised fashion is a ...
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07/10/2018
Handling Incomplete Heterogeneous Data using VAEs
Variational autoencoders (VAEs), as well as other generative models, hav...
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06/06/2018
Boosting Black Box Variational Inference
Approximating a probability density in a tractable manner is a central t...
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05/25/2018
Enhancing the Accuracy and Fairness of Human Decision Making
Societies often rely on human experts to take a wide variety of decision...
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07/26/2017
General Latent Feature Modeling for Data Exploration Tasks
This paper introduces a general Bayesian non- parametric latent feature ...
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06/30/2017
From Parity to Preference-based Notions of Fairness in Classification
The adoption of automated, data-driven decision making in an ever expand...
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06/12/2017
General Latent Feature Models for Heterogeneous Datasets
Latent feature modeling allows capturing the latent structure responsibl...
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10/26/2016
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment
Automated data-driven decision making systems are increasingly being use...
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10/24/2016
Distilling Information Reliability and Source Trustworthiness from Digital Traces
Online knowledge repositories typically rely on their users or dedicated...
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10/18/2016
Modeling the Dynamics of Online Learning Activity
People are increasingly relying on the Web and social media to find solu...
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01/29/2014