4 papers
Higher-Order Causal Structure Learning with Additive Models
James Enouen, Yujia Zheng, Ignavier Ng +2
Causal structure learning has long been the central task of inferring causal insights from data. Despite the abundance of real-world processes exhibiting higher-order mechanisms, h…
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly
James Enouen, Yan Liu
In recent years, the Shapley value and SHAP explanations have emerged as one of the most dominant paradigms for providing post-hoc explanations of black-box models. Despite their w…
Discovering Car-following Dynamics from Trajectory Data through Deep Learning
Ohay Angah, James Enouen, Xuegang +2
This study aims to discover the governing mathematical expressions of car-following dynamics from trajectory data directly using deep learning techniques. We propose an expression…
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments
James Enouen, Tianshu Sun, Yan Liu
Algorithm fairness has become a central problem for the broad adoption of artificial intelligence. Although the past decade has witnessed an explosion of excellent work studying al…