By Dr Reza Argha

Preprints

Sadeghi A; Hajati F; Argha A; Lovell NH; Yang M; Alinejad-Rokny H, 2025, Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking, http://arxiv.org/abs/2505.01696v1

Lee S; Ni S; Wei C; Li S; Fan L; Argha A; Alinejad-Rokny H; Xu R; Gong Y; Yang M, 2025, xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking, http://dx.doi.org/10.48550/arxiv.2501.16727

Hansun S; Argha A; Bakhshayeshi I; Wicaksana A; Alinejad-Rokny H; Fox GJ; Liaw S-T; Celler BG; Marks GB, 2024, Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review (Preprint), http://dx.doi.org/10.2196/preprints.69068

Luo J; Chen L; Luo R; Zhu L; Ao C; Li J; Chen Y; Cheng X; Yang W; Su J; Argha A; Alinejad-Rokny H; Li C; Ni S; Yang M, 2024, PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation, http://dx.doi.org/10.48550/arxiv.2410.01504

Shamsi A; Becirovic R; Argha A; Abbasnejad E; Alinejad-Rokny H; Mohammadi A, 2024, ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance, http://dx.doi.org/10.48550/arxiv.2409.09251

Karami M; Jahanian K; Alizadehsani R; Argha A; Dehzangi I; Gorriz JM; Zhang Y; Hajati F; Yang M; Alinejad-Rokny H, 2023, Revolutionizing Genomics with Reinforcement Learning Techniques, http://dx.doi.org/10.48550/arxiv.2302.13268

Labani M; Beheshti A; Argha A; Alinejad H, 2023, An Integrative Analysis of Chromatin Interactions, Gene Expression and Genomic Variants Identifies 30 Likely Regulatory Variants in Prostate Cancer, http://dx.doi.org/10.20944/preprints202301.0343.v1

Nasab RZ; Ghamsari MRE; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2022, Deep Learning in Spatially Resolved Transcriptomics: A Comprehensive Technical View, http://arxiv.org/abs/2210.04453v3

Hansun S; Argha A; Liaw S-T; Celler BG; Marks GB, 2022, Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review (Preprint), http://dx.doi.org/10.2196/preprints.43154

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