5 papers · 1 filter
CLIMAX: An exploration of Classifier-Based Contrastive Explanations
Praharsh Nanavati, Ranjitha Prasad
Explainable AI is an evolving area that deals with understanding the decision making of machine learning models so that these models are more transparent, accountable, and understa…
DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad +1
Causal structures for observational survival data provide crucial information regarding the relationships between covariates and time-to-event. We derive motivation from the inform…
CAMTA: Causal Attention Model for Multi-touch Attribution
Sachin Kumar, Garima Gupta, Ranjitha Prasad +3
Advertising channels have evolved from conventional print media, billboards and radio advertising to online digital advertising (ad), where the users are exposed to a sequence of a…
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population
Ankit Sharma, Garima Gupta, Ranjitha Prasad +3
Performing inference on data obtained through observational studies is becoming extremely relevant due to the widespread availability of data in fields such as healthcare, educatio…
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework
Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe +1
The holy grail in deep neural network research is porting the memory- and computation-intensive network models on embedded platforms with a minimal compromise in model accuracy. To…