A5103209446- COVID-19 diagnosis using AI
- COVID-19 epidemiological studies
- Advanced Text Analysis Techniques
- SARS-CoV-2 and COVID-19 Research
- Time Series Analysis and Forecasting
- COVID-19 Clinical Research Studies
- Data-Driven Disease Surveillance
- Anomaly Detection Techniques and Applications
- Mental Health Research Topics
- Forecasting Techniques and Applications
- Stock Market Forecasting Methods
University of Georgia
2023
All India Institute of Medical Sciences Rishikesh
2020
Deep Learning has been successfully applied to many application domains, yet its advantages have slow emerge for time series forecasting. For example, in the well-known Makridakis (M) Competitions, hybrids of traditional statistical or machine learning techniques only recently become top performers. With recent architectural advances deep being forecasting (e.g., encoder-decoders with attention, transformers, and graph neural networks), begun show significant advantages. Still, area pandemic...
Deep Learning has been successfully applied to many problem domains, yet its advantages have slow emerge for time series forecasting. For example, in the well-known M Competitions, until recently, hybrids of traditional statistical or machine learning (e.g., gradient boosting) techniques were top performers. With recent architectural advances deep being forecasting, such as encoder-decoders with attention, transformers, representation learning, and graph neural networks, begun show...