5 citations · 19 across the 18 of their papers we have counts for
18 papers
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
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…
Global Cross-Time Attention Fusion for Enhanced Solar Flare Prediction from Multivariate Time Series
Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Multivariate time series classification is increasingly investigated in space weather research as a means to predict intense solar flare events, which can cause widespread disrupti…
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,…
Advancing Minority Stress Detection with Transformers: Insights from the Social Media Datasets
Santosh Chapagain, Cory J Cascalheira, Shah Muhammad Hamdi +2
Individuals from sexual and gender minority groups experience disproportionately high rates of poor health outcomes and mental disorders compared to their heterosexual and cisgende…
Pruning Strategies for Backdoor Defense in LLMs
Santosh Chapagain, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Backdoor attacks are a significant threat to the performance and integrity of pre-trained language models. Although such models are routinely fine-tuned for downstream NLP tasks, r…
Advancing Hate Speech Detection with Transformers: Insights from the MetaHate
Santosh Chapagain, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Hate speech is a widespread and harmful form of online discourse, encompassing slurs and defamatory posts that can have serious social, psychological, and sometimes physical impact…
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…
Predictive Insights into LGBTQ+ Minority Stress: A Transductive Exploration of Social Media Discourse
S. Chapagain, Y. Zhao, T. K. Rohleen +7
Individuals who identify as sexual and gender minorities, including lesbian, gay, bisexual, transgender, queer, and others (LGBTQ+) are more likely to experience poorer health than…
EXCON: Extreme Instance-based Contrastive Representation Learning of Severely Imbalanced Multivariate Time Series for Solar Flare Prediction
Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
In heliophysics research, predicting solar flares is crucial due to their potential to impact both space-based systems and Earth's infrastructure substantially. Magnetic field data…
M-CELS: Counterfactual Explanation for Multivariate Time Series Data Guided by Learned Saliency Maps
Peiyu Li, Omar Bahri, Soukaina Filali Boubrahimi +1
Over the past decade, multivariate time series classification has received great attention. Machine learning (ML) models for multivariate time series classification have made signi…
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…
Info-CELS: Informative Saliency Map Guided Counterfactual Explanation
Peiyu Li, Omar Bahri, Pouya Hosseinzadeh +2
As the demand for interpretable machine learning approaches continues to grow, there is an increasing necessity for human involvement in providing informative explanations for mode…
Contrastive Representation Learning for Predicting Solar Flares from Extremely Imbalanced Multivariate Time Series Data
Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi
Major solar flares are abrupt surges in the Sun's magnetic flux, presenting significant risks to technological infrastructure. In view of this, effectively predicting major flares…
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…
Motif-guided Time Series Counterfactual Explanations
Peiyu Li, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi
With the rising need of interpretable machine learning methods, there is a necessity for a rise in human effort to provide diverse explanations of the influencing factors of the mo…
Shapelet-Based Counterfactual Explanations for Multivariate Time Series
Omar Bahri, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi
As machine learning and deep learning models have become highly prevalent in a multitude of domains, the main reservation in their adoption for decision-making processes is their b…