146 citations · 646 across the 40 of their papers we have counts for
9 papers · 1 filter
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya +2
Logical reasoning over Knowledge Graphs (KGs) is a fundamental technique that can provide efficient querying mechanism over large and incomplete databases. Current approaches emplo…
Supervised Contrastive Learning for Interpretable Long-Form Document Matching
Akshita Jha, Vineeth Rakesh, Jaideep Chandrashekar +2
Recent advancements in deep learning techniques have transformed the area of semantic text matching. However, most state-of-the-art models are designed to operate with short docume…
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes
Ping Wang, Tian Shi, Khushbu Agarwal +2
Question Answering (QA) in clinical notes has gained a lot of attention in the past few years. Existing machine reading comprehension approaches in clinical domain can only handle…
Fair Representation Learning using Interpolation Enabled Disentanglement
Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy
With the growing interest in the machine learning community to solve real-world problems, it has become crucial to uncover the hidden reasoning behind their decisions by focusing o…
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series
Sindhu Tipirneni, Chandan K. Reddy
Multivariate time-series data are frequently observed in critical care settings and are typically characterized by sparsity (missing information) and irregular time intervals. Exis…
Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction
Chang Lu, Chandan K. Reddy, Yue Ning
Electronic Health Records (EHR) have been heavily used in modern healthcare systems for recording patients' admission information to hospitals. Many data-driven approaches employ t…
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
Chang Lu, Chandan K. Reddy, Prithwish Chakraborty +2
Accurate and explainable health event predictions are becoming crucial for healthcare providers to develop care plans for patients. The availability of electronic health records (E…
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
Neal Mangaokar, Jiameng Pu, Parantapa Bhattacharya +2
Advances in deep neural networks (DNNs) have shown tremendous promise in the medical domain. However, the deep learning tools that are helping the domain, can also be used against…
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification
Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed +5
Deep Neural Network (DNN) classifiers are known to be vulnerable to Trojan or backdoor attacks, where the classifier is manipulated such that it misclassifies any input containing…