3 citations · 4 across the 3 of their papers we have counts for
7 papers
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings
Utkarsh Sarawgi, Rishab Khincha, Wazeer Zulfikar +2
Reliability of machine learning (ML) systems is crucial in safety-critical applications such as healthcare, and uncertainty estimation is a widely researched method to highlight th…
Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks
Rishab Khincha, Utkarsh Sarawgi, Wazeer Zulfikar +1
The problem of missing data has been persistent for a long time and poses a major obstacle in machine learning and statistical data analysis. Past works in this field have tried us…
Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia
Utkarsh Sarawgi, Wazeer Zulfikar, Rishab Khincha +1
Reliability in Neural Networks (NNs) is crucial in safety-critical applications like healthcare, and uncertainty estimation is a widely researched method to highlight the confidenc…
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles
Utkarsh Sarawgi, Wazeer Zulfikar, Rishab Khincha +1
Understanding and quantifying uncertainty in black box Neural Networks (NNs) is critical when deployed in real-world settings such as healthcare. Recent works using Bayesian and no…
Multimodal Inductive Transfer Learning for Detection of Alzheimer's Dementia and its Severity
Utkarsh Sarawgi, Wazeer Zulfikar, Nouran Soliman +1
Alzheimer's disease is estimated to affect around 50 million people worldwide and is rising rapidly, with a global economic burden of nearly a trillion dollars. This calls for scal…
Towards Task Understanding in Visual Settings
Sebastin Santy, Wazeer Zulfikar, Rishabh Mehrotra +1
We consider the problem of understanding real world tasks depicted in visual images. While most existing image captioning methods excel in producing natural language descriptions o…