5 citations · 5 across the 2 of their papers we have counts for
3 papers
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations
Rachana Balasubramanian, Samuel Sharpe, Brian Barr +2
In the environment of fair lending laws and the General Data Protection Regulation (GDPR), the ability to explain a model's prediction is of paramount importance. High quality expl…
Machine Learning for Temporal Data in Finance: Challenges and Opportunities
Jason Wittenbach, Brian d'Alessandro, C. Bayan Bruss
Temporal data are ubiquitous in the financial services (FS) industry -- traditional data like economic indicators, operational data such as bank account transactions, and modern da…
Towards Ground Truth Explainability on Tabular Data
Brian Barr, Ke Xu, Claudio Silva +4
In data science, there is a long history of using synthetic data for method development, feature selection and feature engineering. Our current interest in synthetic data comes fro…