6 papers
SolarGPT-QA: A Domain-Adaptive Large Language Model for Educational Question Answering in Space Weather and Heliophysics
Santosh Chapagain, MohammadReza EskandariNasab, Onur Vural +2
Solar activity, including solar flares, coronal mass ejections (CMEs), and geomagnetic storms can significantly impact satellites, aviation, power grids, data centers, and space mi…
TIMED: Adversarial and Autoregressive Refinement of Diffusion-Based Time Series Generation
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Generating high-quality synthetic time series is a fundamental yet challenging task across domains such as forecasting and anomaly detection, where real data can be scarce, noisy,…
AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Data augmentation can significantly enhance the performance of machine learning tasks by addressing data scarcity and improving generalization. However, generating time series data…
SeriesGAN: Time Series Generation via Adversarial and Autoregressive Learning
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Current Generative Adversarial Network (GAN)-based approaches for time series generation face challenges such as suboptimal convergence, information loss in embedding spaces, and i…
Enhancing Multivariate Time Series-based Solar Flare Prediction with Multifaceted Preprocessing and Contrastive Learning
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Accurate solar flare prediction is crucial due to the significant risks that intense solar flares pose to astronauts, space equipment, and satellite communication systems. Our rese…
ChronoGAN: Supervised and Embedded Generative Adversarial Networks for Time Series Generation
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Generating time series data using Generative Adversarial Networks (GANs) presents several prevalent challenges, such as slow convergence, information loss in embedding spaces, inst…