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07/02/2023
CLIMAX: An exploration of Classifier-Based Contrastive Explanations
Explainable AI is an evolving area that deals with understanding the dec...
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11/07/2022
Over-The-Air Clustered Wireless Federated Learning
Privacy, security, and bandwidth constraints have led to federated learn...
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11/02/2021
DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
Causal structures for observational survival data provide crucial inform...
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08/16/2021
Locally Interpretable Model Agnostic Explanations using Gaussian Processes
Owing to tremendous performance improvements in data-intensive domains, ...
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05/26/2021
Path-Aware OMP Algorithms for Provenance Recovery in Vehicular Networks
Low-latency provenance embedding methods have received traction in vehic...
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01/01/2021
B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning
There is a growing interest in the learning-to-learn paradigm, also know...
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08/22/2020
Hi-CI: Deep Causal Inference in High Dimensions
We address the problem of counterfactual regression using causal inferen...
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04/28/2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks
Causal inference (CI) in observational studies has received a lot of att...
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12/09/2019
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population
Performing inference on data obtained through observational studies is b...
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10/26/2019
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework
The holy grail in deep neural network research is porting the memory- an...
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02/02/2018
Unlabelled Sensing: A Sparse Bayesian Learning Approach
We address the recovery of sparse vectors in an overcomplete, linear and...
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02/06/2012
