Simultaneous Segmentation of Multiple Retinal Pathologies Using Fully Convolutional Deep Neural Network. - Maryam Badar; Muhammad Shahzad 002; M. M. Fraz 001 (MIUA, 2018)

Modeling Safest and Optimal Emergency Evacuation Plan for Large-Scale Pedestrians Environments. - Muhammad Haris 001; Imran Mahmood; Maryam Badar; Muhammad Saad Qaisar Alvi (WSC, 2018)

Application of deep learning for retinal image analysis: A review. - Maryam Badar; Muhammad Haris 001; Anam Fatima (Comput. Sci. Rev., 2020)

Discrimination and Class Imbalance Aware Online Naive Bayes. - Maryam Badar; Marco Fisichella; Vasileios Iosifidis; Wolfgang Nejdl (CoRR, 2022)

A Review of the Role of Causality in Developing Trustworthy AI Systems. - Niloy Ganguly; Dren Fazlija; Maryam Badar; Marco Fisichella; Sandipan Sikdar; Johanna Schrader; Jonas Wallat; Koustav Rudra; Manolis Koubarakis; Gourab K. Patro; Wadhah Zai El Amri; Wolfgang Nejdl (CoRR, 2023)

FAC-fed: Federated adaptation for fairness and concept drift aware stream classification. - Maryam Badar; Wolfgang Nejdl; Marco Fisichella (Mach. Learn., 2023)

FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning. - Maryam Badar; Sandipan Sikdar; Wolfgang Nejdl; Marco Fisichella (AAAI, 2024)

TrustFed: Navigating Trade-offs Between Performance, Fairness, and Privacy in Federated Learning. - Maryam Badar; Sandipan Sikdar; Wolfgang Nejdl; Marco Fisichella (ECAI, 2024)

Fair-CMNB: Advancing Fairness-Aware Stream Learning with Naïve Bayes and Multi-Objective Optimization. - Maryam Badar; Marco Fisichella (Big Data Cogn. Comput., 2024)