2 papers
cs.LG2025
TIE: A Training-Inversion-Exclusion Framework for Visually Interpretable and Uncertainty-Guided Out-of-Distribution Detection
Pirzada Suhail, Rehna Afroz, Amit Sethi
Deep neural networks often struggle to recognize when an input lies outside their training experience, leading to unreliable and overconfident predictions. Building dependable mach…
cs.LG2025
Network Inversion for Uncertainty-Aware Out-of-Distribution Detection
Pirzada Suhail, Rehna Afroz, Gouranga Bala +1
Out-of-distribution (OOD) detection and uncertainty estimation (UE) are critical components for building safe machine learning systems, especially in real-world scenarios where une…