1.3k citations · 22.7k across the 126 of their papers we have counts for
128 papers
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms
Gareth P. Jones, James M. Hickey, Pietro G. Di Stefano +3
Understanding and removing bias from the decisions made by machine learning models is essential to avoid discrimination against unprivileged groups. Despite recent progress in algo…
Fairness by Explicability and Adversarial SHAP Learning
James M. Hickey, Pietro G. Di Stefano, Vlasios Vasileiou
The ability to understand and trust the fairness of model predictions, particularly when considering the outcomes of unprivileged groups, is critical to the deployment and adoption…
Counterfactual fairness: removing direct effects through regularization
Pietro G. Di Stefano, James M. Hickey, Vlasios Vasileiou
Building machine learning models that are fair with respect to an unprivileged group is a topical problem. Modern fairness-aware algorithms often ignore causal effects and enforce…
Swift and Fermi observations of X-ray flares: the case of Late Internal Shock
E. Troja, L. Piro, V. Vasileiou +5
Simultaneous Swift and Fermi observations of gamma-ray bursts (GRBs) offer a unique broadband view of their afterglow emission, spanning more than ten decades in energy. We present…
Gamma-ray flaring activity from the gravitationally lensed blazar PKS 1830-211 observed by Fermi LAT
The Fermi LAT Collaboration, A. A. Abdo, M. Ackermann +126
The Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope routinely detects the highly dust-absorbed, reddened, and MeV-peaked flat spectrum radio quasar PKS 1830…
Milagro Limits and HAWC Sensitivity for the Rate-Density of Evaporating Primordial Black Holes
A. A. Abdo, A. U. Abeysekara, R. Alfaro +118
Primordial Black Holes (PBHs) are gravitationally collapsed objects that may have been created by density fluctuations in the early universe and could have arbitrarily small masses…