Explainable AI is an evolving area that deals with understanding the dec...
Privacy, security, and bandwidth constraints have led to federated learn...
Causal structures for observational survival data provide crucial inform...
Owing to tremendous performance improvements in data-intensive domains,
...
Low-latency provenance embedding methods have received traction in vehic...
There is a growing interest in the learning-to-learn paradigm, also know...
We address the problem of counterfactual regression using causal inferen...
Causal inference (CI) in observational studies has received a lot of
att...
Performing inference on data obtained through observational studies is
b...
The holy grail in deep neural network research is porting the memory- an...
We address the recovery of sparse vectors in an overcomplete, linear and...
In this paper, we derive Hybrid, Bayesian and Marginalized Cramér-Rao
lo...