4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2025
RobustX: Robust Counterfactual Explanations Made Easy
Junqi Jiang, Luca Marzari, Aaryan Purohit +1
The increasing use of Machine Learning (ML) models to aid decision-making in high-stakes industries demands explainability to facilitate trust. Counterfactual Explanations (CEs) ar…
cs.LG2025★ 4 cited
Explainable Reinforcement Learning for Formula One Race Strategy
Devin Thomas, Junqi Jiang, Avinash Kori +6
In Formula One, teams compete to develop their cars and achieve the highest possible finishing position in each race. During a race, however, teams are unable to alter the car, so…
cs.LG2025★ 3 cited
Explainable Time Series Prediction of Tyre Energy in Formula One Race Strategy
Jamie Todd, Junqi Jiang, Aaron Russo +4
Formula One (F1) race strategy takes place in a high-pressure and fast-paced environment where split-second decisions can drastically affect race results. Two of the core decisions…