2 citations · 3 across the 5 of their papers we have counts for
6 papers
Conformal Adversarial Generative Ensemble
Ahmad Shahi, Mamehgol Yousefi, Brendon J. Woodford +2
Accurate time series forecasting is critical across various domains, yet traditional ensemble methods often suffer from the disproportionate influence of extreme forecasts. We intr…
Adaptive Conformal Redistribution for Inter-class Transitional Uncertainty in Medical Image Classification
Saibal Ghosh, Samarup Bhattacharya, Sanjoy Kumar Saha +2
Medical image classification is frequently complicated by transitional categories whose feature distributions overlap those of adjacent classes, producing ambiguous decision bounda…
AI Generalisation Gap In Comorbid Sleep Disorder Staging
Saswata Bose, Suvadeep Maiti, Shivam Kumar Sharma +4
Accurate sleep staging is essential for diagnosing OSA and hypopnea in stroke patients. Although PSG is reliable, it is costly, labor-intensive, and manually scored. While deep lea…
Leakage and Interpretability in Concept-Based Models
Enrico Parisini, Tapabrata Chakraborti, Chris Harbron +2
Concept-based Models aim to improve interpretability by predicting high-level intermediate concepts, representing a promising approach for deployment in high-risk scenarios. Howeve…
Generating crossmodal gene expression from cancer histopathology improves multimodal AI predictions
Samiran Dey, Christopher R. S. Banerji, Partha Basuchowdhuri +3
Emerging research has highlighted that artificial intelligence-based multimodal fusion of digital pathology and transcriptomic features can improve cancer diagnosis (grading/subtyp…
Deep Learning as Ricci Flow
Anthony Baptista, Alessandro Barp, Tapabrata Chakraborti +3
Deep neural networks (DNNs) are powerful tools for approximating the distribution of complex data. It is known that data passing through a trained DNN classifier undergoes a series…