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02/20/2023
Neural Algorithmic Reasoning with Causal Regularisation
Recent work on neural algorithmic reasoning has investigated the reasoni...
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10/24/2022
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data
High model performance, on average, can hide that models may systematica...
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10/08/2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation
Consider the problem of improving the estimation of conditional average ...
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08/02/2022
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction
Leveraging labelled data from multiple domains to enable prediction in a...
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06/16/2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
Estimating personalized effects of treatments is a complex, yet pervasiv...
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01/13/2022
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
Despite recent progress made by self-supervised methods in representatio...
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12/07/2021
Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time
Choosing the best treatment-plan for each individual patient requires ac...
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06/08/2021
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
Understanding decision-making in clinical environments is of paramount i...
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02/23/2021
Model-Attentive Ensemble Learning for Sequence Modeling
Medical time-series datasets have unique characteristics that make predi...
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02/11/2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge
Selecting causal inference models for estimating individualized treatmen...
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01/28/2021
Learning Matching Representations for Individualized Organ Transplantation Allocation
Organ transplantation is often the last resort for treating end-stage il...
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06/25/2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching
Consider learning a policy purely on the basis of demonstrated behavior—...
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02/27/2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
While much attention has been given to the problem of estimating the eff...
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02/10/2020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
Identifying when to give treatments to patients and how to select among ...
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02/01/2019
