36 citations · 37 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Revealing Unfair Models by Mining Interpretable Evidence
Mohit Bajaj, Lingyang Chu, Vittorio Romaniello +5
The popularity of machine learning has increased the risk of unfair models getting deployed in high-stake applications, such as justice system, drug/vaccination design, and medical…
cs.LG2021★ 36 cited
Robust Counterfactual Explanations on Graph Neural Networks
Mohit Bajaj, Lingyang Chu, Zi Yu Xue +4
Massive deployment of Graph Neural Networks (GNNs) in high-stake applications generates a strong demand for explanations that are robust to noise and align well with human intuitio…