8 papers · 1 filter
Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies
Arun Kumar Selvaraj, Tanay Panat, Rohitash Chandra
The drastic changes in the global economy, geopolitical conditions, and disruptions such as the COVID-19 pandemic have impacted the cost of living and quality of life. It is essent…
DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection
Omkar Kulkarni, Rohitash Chandra
Financial fraud detection is critical for maintaining the integrity of financial systems, particularly in decentralised environments such as cryptocurrency networks. Although Graph…
Extreme value forecasting using relevance-based data augmentation with deep learning models
Junru Hua, Rahul Ahluwalia, Rohitash Chandra
Data augmentation with generative adversarial networks (GANs) has been popular for class imbalance problems, mainly for pattern classification and computer vision-related applicati…
Spatiotemporal deep learning models for detection of rapid intensification in cyclones
Vamshika Sutar, Amandeep Singh, Rohitash Chandra
Cyclone rapid intensification is the rapid increase in cyclone wind intensity, exceeding a threshold of 30 knots, within 24 hours. Rapid intensification is considered an extreme ev…
Ensemble quantile-based deep learning framework for streamflow and flood prediction in Australian catchments
Rohitash Chandra, Arpit Kapoor, Siddharth Khedkar +2
In recent years, climate extremes such as floods have created significant environmental and economic hazards for Australia. Deep learning methods have been promising for predicting…
A Machine Learning Framework for Handling Unreliable Absence Label and Class Imbalance for Marine Stinger Beaching Prediction
Amuche Ibenegbu, Amandine Schaeffer, Pierre Lafaye de Micheaux +1
Bluebottles (\textit{Physalia} spp.) are marine stingers resembling jellyfish, whose presence on Australian beaches poses a significant public risk due to their venomous nature. Un…