Fitted Learning: Models with Awareness of their Limits. - Navid Kardan; Kenneth O. Stanley (CoRR, 2016)

Mitigating fooling with competitive overcomplete output layer neural networks. - Navid Kardan; Kenneth O. Stanley (IJCNN, 2017)

Towards Consistent Predictive Confidence through Fitted Ensembles. - Navid Kardan; Ankit Sharma; Kenneth O. Stanley (IJCNN, 2021)

Advances in Adversarial Attacks and Defenses in Computer Vision: A Survey. - Naveed Akhtar; Ajmal Mian; Navid Kardan; Mubarak Shah (IEEE Access, 2021)

Threat of Adversarial Attacks on Deep Learning in Computer Vision: Survey II. - Naveed Akhtar; Ajmal Mian; Navid Kardan; Mubarak Shah (CoRR, 2021)

OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning. - Mamshad Nayeem Rizve; Navid Kardan; Salman Khan 001; Fahad Shahbaz Khan; Mubarak Shah (ECCV (31), 2022)

Towards Realistic Semi-supervised Learning. - Mamshad Nayeem Rizve; Navid Kardan; Mubarak Shah (ECCV (31), 2022)

Self-Joint Supervised Learning. - Navid Kardan; Mubarak Shah; Mitch Hill (ICLR, 2022)

Detecting Compromised Architecture/Weights of a Deep Model. - James Beetham; Navid Kardan; Ajmal Mian; Mubarak Shah (ICPR, 2022)

CDFSL-V: Cross-Domain Few-Shot Learning for Videos. - Sarinda Samarasinghe; Mamshad Nayeem Rizve; Navid Kardan; Mubarak Shah (ICCV, 2023)

Dual Student Networks for Data-Free Model Stealing. - James Beetham; Navid Kardan; Ajmal Saeed Mian; Mubarak Shah (ICLR, 2023)