Md Abdur Rahaman

16 papers C 1Journal 5Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Punching Above Precision: Small Quantized Model Distillation with Learnable Regularizer. CoRR Abdur Rehman, SMA Sharif, Md Abdur Rahaman, M. J. Aashik Rasool, Seongwan Kim, Jaeho Lee
2024	—	`conf`	A Deep Biclustering Framework for Brain Network Analysis. CVPR Workshops Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun
2024	J	`jnl`	A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. Brain Connect. Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Jingyu Liu, Vince D. Calhoun
2024	J	`jnl`	An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. CoRR Giorgio Dolci, Federica Cruciani, Md Abdur Rahaman, Anees Abrol, Jiayu Chen, Zening Fu, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun
2024	—	`conf`	SpaDE: Semantic Locality Preserving Biclustering for Neuroimaging Data. EMBC Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun
2023	—	`conf`	Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. ICASSP Workshops Giorgio Dolci, Md Abdur Rahaman, Ilaria Boscolo Galazzo, Federica Cruciani, Anees Abrol, Jiayu Chen, Zening Fu, Kuaikuai Duan, Gloria Menegaz, Vince D. Calhoun
2022	C	`conf`	A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. BIBE Giorgio Dolci, Md Abdur Rahaman, Jiayu Chen, Kuaikuai Duan, Zening Fu, Anees Abrol, Gloria Menegaz, Vince D. Calhoun
2022	—	`conf`	Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data. ISBI Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Vince D. Calhoun
2022	—	`conf`	Performance Analysis between YOLOv5s and YOLOv5m Model to Detect and Count Blood Cells: Deep Learning Approach. ICCA Md Abdur Rahaman, Md Mamun Ali, Kawsar Ahmed, Francis M. Bui, S. M. Hasan Mahmud
2022	J	`jnl`	Tri-Clustering Dynamic Functional Network Connectivity Identifies Significant Schizophrenia Effects Across Multiple States in Distinct Subgroups of Individuals. Brain Connect. Md Abdur Rahaman, Eswar Damaraju, Jessica A. Turner, Theo G. M. van Erp, Daniel H. Mathalon, Jatin G. Vaidya, Bryon A. Mueller, Godfrey D. Pearlson, Vince D. Calhoun
2022	—	`conf`	Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data. MLSP Md Abdur Rahaman, Yash Garg, Armin Iraji, Zening Fu, Jiayu Chen, Vince D. Calhoun
2021	—	`conf`	DCBC_DeepL: Detection and Counting of Blood Cells Employing Deep Learning and YOLOv5 Model. ICAIDS Md Abdur Rahaman, Md Mamun Ali, Md. Nazmul Hossen, Md. Nayer, Kawsar Ahmed, Francis M. Bui
2021	—	`conf`	Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness. EMBC Md Abdur Rahaman, Jiayu Chen, Zening Fu, Noah Lewis, Armin Iraji, Vince D. Calhoun
2021	—	`conf`	Shared sets of correlated polygenic risk scores and voxel-wise grey matter across multiple traits identified via bi-clustering. EMBC Md Abdur Rahaman, Amanda Rodrigue, David C. Glahn, Jessica A. Turner, Vince D. Calhoun
2021	—	`conf`	Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. ISBI Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Vince D. Calhoun, Sergey M. Plis
2020	J	`jnl`	N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia. IEEE Trans. Biomed. Eng. Md Abdur Rahaman, Daniel H. Mathalon, Hyo Jong Lee, Wenhao Jiang, Bryon A. Mueller, Ole A. Andreassen, Ingrid Agartz, Scott R. Sponheim, Andrew R. Mayer, Julia M. Stephen, Rex E. Jung, Jessica A. Turner, José M. Cañive, Juan R. Bustillo, Vince D. Calhoun, Cota Navin Gupta, Srinivas Rachakonda, Jiayu Chen, Jingyu Liu, Theo G. M. van Erp, Steven G. Potkin, Judith M. Ford