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ORCIDArchana Venkataraman
- > Home > Persons > Archana Venkataraman
Publications
- 2023
[c38]Niharika Shimona D'Souza, Archana Venkataraman:
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. IPMI 2023: 53-65- [i17]Niharika Shimona D'Souza, Archana Venkataraman:
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. CoRR abs/2303.14986 (2023) - 2021
- [j6]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. NeuroImage 241: 118388 (2021) - [c31]Yu-Chung Peng, Niharika Shimona D'Souza, Brian Bush, Charles Brown, Archana Venkataraman:
Predicting Acute Kidney Injury via Interpretable Ensemble Learning and Attention Weighted Convoutional-Recurrent Neural Networks. CISS 2021: 1-6 - [c29]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. MICCAI (7) 2021: 625-636 - [c28]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
M-GCN: A Multimodal Graph Convolutional Network to Integrate Functional and Structural Connectomics Data to Predict Multidimensional Phenotypic Characterizations. MIDL 2021: 119-130 - [i12]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. CoRR abs/2105.14409 (2021) - 2020
- [j5]Niharika Shimona D'Souza, Mary Beth Nebel
, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A joint network optimization framework to predict clinical severity from resting state functional MRI data. NeuroImage 206 (2020) - [c24]Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. MLCN/RNO-AI@MICCAI 2020: 34-44 - [c23]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. MICCAI (7) 2020: 437-447 - [i9]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. CoRR abs/2007.01929 (2020) - [i8]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. CoRR abs/2007.01930 (2020) - [i7]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. CoRR abs/2007.01931 (2020) - [i4]Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart H. Mostofsky, Archana Venkataraman:
Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations. CoRR abs/2008.12410 (2020) - [i3]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman:
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data. CoRR abs/2009.03238 (2020) - [i2]Naresh Nandakumar, Niharika Shimona D'Souza, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity. CoRR abs/2011.08813 (2020) - 2019
- [c17]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI 2019: 605-616 - [c13]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) 2019: 709-717 - 2018
- [c11]Naresh Nandakumar, Niharika Shimona D'Souza, Jeff Craley, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman:
Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields. CNI@MICCAI 2018: 88-98 - [c10]Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman:
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) 2018: 163-171
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