7 citations · 11 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
One-way Explainability Isn't The Message
Ashwin Srinivasan, Michael Bain, Enrico Coiera
Recent engineering developments in specialised computational hardware, data-acquisition and storage technology have seen the emergence of Machine Learning (ML) as a powerful form o…
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems
Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash +3
The ability to recognise and make analogies is often used as a measure or test of human intelligence. The ability to solve Bongard problems is an example of such a test. It has als…
Incorporating Symbolic Domain Knowledge into Graph Neural Networks
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig
Our interest is in scientific problems with the following characteristics: (1) Data are naturally represented as graphs; (2) The amount of data available is typically small; and (3…
Logical Explanations for Deep Relational Machines Using Relevance Information
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
Our interest in this paper is in the construction of symbolic explanations for predictions made by a deep neural network. We will focus attention on deep relational machines (DRMs,…