3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.LG2021★ 3 cited
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation
Mohammed Temraz, Mark T. Keane
Learning from class imbalanced datasets poses challenges for many machine learning algorithms. Many real-world domains are, by definition, class imbalanced by virtue of having a ma…
cs.AI2021
Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future
Mohammed Temraz, Eoin Kenny, Elodie Ruelle +3
Climate change poses a major challenge to humanity, especially in its impact on agriculture, a challenge that a responsible AI should meet. In this paper, we examine a CBR system (…
cs.AI2021
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation
Mark T Keane, Eoin M Kenny, Mohammed Temraz +2
Recently, it has been proposed that fruitful synergies may exist between Deep Learning (DL) and Case Based Reasoning (CBR); that there are insights to be gained by applying CBR ide…