183 citations · 474 across the 24 of their papers we have counts for
24 papers
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification
Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash +6
Deep neural network (DNN) models for retinopathy have estimated predictive accuracies in the mid-to-high 90%. However, the following aspects remain unaddressed: State-of-the-art mo…
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification
Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash +5
Whole Slide Images (WSIs) or histopathology images are used in digital pathology. WSIs pose great challenges to deep learning models for clinical diagnosis, owing to their size and…
Neuro-symbolic Meta Reinforcement Learning for Trading
S I Harini, Gautam Shroff, Ashwin Srinivasan +2
We model short-duration (e.g. day) trading in financial markets as a sequential decision-making problem under uncertainty, with the added complication of continual concept-drift. W…
A Model for Intelligible Interaction Between Agents That Predict and Explain
A. Baskar, Ashwin Srinivasan, Michael Bain +1
Machine Learning (ML) has emerged as a powerful form of data modelling with widespread applicability beyond its roots in the design of autonomous agents. However, relatively little…
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss
Vedant Shah, Aditya Agrawal, Lovekesh Vig +3
We are interested in neurosymbolic systems consisting of a high-level symbolic layer for explainable prediction in terms of human-intelligible concepts; and a low-level neural laye…
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
Vishwa Shah, Aditya Sharma, Gautam Shroff +3
Analogical Reasoning problems challenge both connectionist and symbolic AI systems as these entail a combination of background knowledge, reasoning and pattern recognition. While s…