1 citations · 1 across the 1 of their papers we have counts for
8 papers
A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets
Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel +1
Health mention classification deals with the disease detection in a given text containing disease words. However, non-health and figurative use of disease words adds challenges to…
Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training
Pervaiz Iqbal Khan, Shoaib Ahmed Siddiqui, Imran Razzak +2
Health mentioning classification (HMC) classifies an input text as health mention or not. Figurative and non-health mention of disease words makes the classification task challengi…
Utilizing Out-Domain Datasets to Enhance Multi-Task Citation Analysis
Dominique Mercier, Syed Tahseen Raza Rizvi, Vikas Rajashekar +2
Citations are generally analyzed using only quantitative measures while excluding qualitative aspects such as sentiment and intent. However, qualitative aspects provide deeper insi…
KENN: Enhancing Deep Neural Networks by Leveraging Knowledge for Time Series Forecasting
Muhammad Ali Chattha, Ludger van Elst, Muhammad Imran Malik +2
End-to-end data-driven machine learning methods often have exuberant requirements in terms of quality and quantity of training data which are often impractical to fulfill in real-w…
Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods
Dominique Mercier, Jwalin Bhatt, Andreas Dengel +1
In the last decade neural network have made huge impact both in industry and research due to their ability to extract meaningful features from imprecise or complex data, and by ach…
TimeREISE: Time-series Randomized Evolving Input Sample Explanation
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are one of the most successful classifiers across different domains. However, due to their limitations concerning interpretability their use is limited in safe…