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Nicholas F. Wymbs
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2020 – today
- 2021
- [j9]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) - [i8]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
- [j8]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) - [c7]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 - [i7]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) - [i6]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) - [i5]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)
2010 – 2019
- 2019
- [j7]Brian A. Mitchell, Nina Lauharatanahirun, Javier O. Garcia, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Vettel, Linda R. Petzold:
A Minimum Free Energy Model of Motor Learning. Neural Comput. 31(10): 1945-1963 (2019) - [c6]Niharika Shimona D'Souza, Mary Beth Nebel
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI 2019: 605-616 - [c5]Niharika Shimona D'Souza, Mary Beth Nebel
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) 2019: 709-717 - 2018
- [j6]Ankit N. Khambhati
Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration. NeuroImage 166: 385-399 (2018) - [j5]Pranav G. Reddy, Marcelo Gomes Mattar, Andrew C. Murphy
Brain state flexibility accompanies motor-skill acquisition. NeuroImage 171: 135-147 (2018) - [j4]Marcelo Gomes Mattar, Nicholas F. Wymbs, Andrew S. Bock, Geoffrey Karl Aguirre, Scott T. Grafton, Danielle S. Bassett:
Predicting future learning from baseline network architecture. NeuroImage 172: 107-117 (2018) - [c4]Niharika Shimona D'Souza, Mary Beth Nebel
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) 2018: 163-171 - 2017
- [c3]Leah Goldsberry, Weiyu Huang, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro
Brain signal analytics from graph signal processing perspective. ICASSP 2017: 851-855 - [c2]Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel
A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. CNI@MICCAI 2017: 60-69 - 2016
- [j3]Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro
Graph Frequency Analysis of Brain Signals. IEEE J. Sel. Top. Signal Process. 10(7): 1189-1203 (2016) - [c1]Firas Mawase
Reward gain model describes cortical use-dependent plasticity. EMBC 2016: 5-8 - 2015
- [i2]Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro:
Graph Frequency Analysis of Brain Signals. CoRR abs/1512.00037 (2015) - 2013
- [j2]Alexander V. Mantzaris
Dynamic network centrality summarizes learning in the human brain. J. Complex Networks 1(1): 83-92 (2013) - [j1]Danielle S. Bassett, Nicholas F. Wymbs, M. Puck Rombach, Mason A. Porter, Peter J. Mucha, Scott T. Grafton:
Task-Based Core-Periphery Organization of Human Brain Dynamics. PLoS Comput. Biol. 9(9) (2013) - 2012
- [i1]Danielle S. Bassett, Mason A. Porter, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Carlson, Peter J. Mucha:
Robust Detection of Dynamic Community Structure in Networks. CoRR abs/1206.4358 (2012)
Coauthor Index
aka: Stewart Mostofsky
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