1 citations · 1 across the 5 of their papers we have counts for
5 papers
Rescuing referral failures during automated diagnosis of domain-shifted medical images
Anuj Srivastava, Karm Patel, Pradeep Shenoy +1
The success of deep learning models deployed in the real world depends critically on their ability to generalize well across diverse data domains. Here, we address a fundamental ch…
Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++
Barath Mohan Umapathi, Kushal Chauhan, Pradeep Shenoy +1
Reliable outlier detection is critical for real-world deployment of deep learning models. Although extensively studied, likelihoods produced by deep generative models have been lar…
Matching options to tasks using Option-Indexed Hierarchical Reinforcement Learning
Kushal Chauhan, Soumya Chatterjee, Akash Reddy +2
The options framework in Hierarchical Reinforcement Learning breaks down overall goals into a combination of options or simpler tasks and associated policies, allowing for abstract…
Robust outlier detection by de-biasing VAE likelihoods
Kushal Chauhan, Barath Mohan U, Pradeep Shenoy +2
Deep networks often make confident, yet, incorrect, predictions when tested with outlier data that is far removed from their training distributions. Likelihoods computed by deep ge…
Model-agnostic Fits for Understanding Information Seeking Patterns in Humans
Soumya Chatterjee, Pradeep Shenoy
In decision making tasks under uncertainty, humans display characteristic biases in seeking, integrating, and acting upon information relevant to the task. Here, we reexamine data…