Nicholas F. Wymbs

24 papers Misc 1Journal 17Unranked 6

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
2021	J	`jnl`	Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations. NeuroImage Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Joshua Robinson, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
2020	J	`jnl`	A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
2020	—	`conf`	A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. MICCAI (7) Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
2020	J	`jnl`	A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman
2020	J	`jnl`	A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
2020	J	`jnl`	A joint network optimization framework to predict clinical severity from resting state functional MRI data. NeuroImage Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart H. Mostofsky, Archana Venkataraman
2020	J	`jnl`	Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart H. Mostofsky, Archana Venkataraman
2020	J	`jnl`	Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. CoRR Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
2019	—	`conf`	A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. IPMI Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
2019	J	`jnl`	A Minimum Free Energy Model of Motor Learning. Neural Comput. Brian A. Mitchell, Nina Lauharatanahirun, Javier O. Garcia, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Vettel, Linda R. Petzold
2019	—	`conf`	Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. MICCAI (3) Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
2018	—	`conf`	A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. MICCAI (3) Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas F. Wymbs, Stewart Mostofsky, Archana Venkataraman
2018	J	`jnl`	Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration. NeuroImage Ankit N. Khambhati, Marcelo Gomes Mattar, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett
2018	J	`jnl`	Brain state flexibility accompanies motor-skill acquisition. NeuroImage Pranav G. Reddy, Marcelo Gomes Mattar, Andrew C. Murphy, Nicholas F. Wymbs, Scott T. Grafton, Theodore D. Satterthwaite, Danielle S. Bassett
2018	J	`jnl`	Predicting future learning from baseline network architecture. NeuroImage Marcelo Gomes Mattar, Nicholas F. Wymbs, Andrew S. Bock, Geoffrey Karl Aguirre, Scott T. Grafton, Danielle S. Bassett
2017	—	`conf`	A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. CNI@MICCAI Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel, Stewart Mostofsky
2017	Misc	`conf`	Brain signal analytics from graph signal processing perspective. ICASSP Leah Goldsberry, Weiyu Huang, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro
2016	J	`jnl`	Graph Frequency Analysis of Brain Signals. IEEE J. Sel. Top. Signal Process. Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro
2016	—	`conf`	Reward gain model describes cortical use-dependent plasticity. EMBC Firas Mawase, Nicholas F. Wymbs, Shintaro Uehara, Pablo Celnik
2015	J	`jnl`	Graph Frequency Analysis of Brain Signals. CoRR Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett, Alejandro Ribeiro
2013	J	`jnl`	Dynamic network centrality summarizes learning in the human brain. J. Complex Networks Alexander V. Mantzaris, Danielle S. Bassett, Nicholas F. Wymbs, Ernesto Estrada, Mason A. Porter, Peter J. Mucha, Scott T. Grafton, Desmond J. Higham
2013	J	`jnl`	Task-Based Core-Periphery Organization of Human Brain Dynamics. PLoS Comput. Biol. Danielle S. Bassett, Nicholas F. Wymbs, M. Puck Rombach, Mason A. Porter, Peter J. Mucha, Scott T. Grafton
2012	J	`jnl`	Robust Detection of Dynamic Community Structure in Networks CoRR Danielle S. Bassett, Mason A. Porter, Nicholas F. Wymbs, Scott T. Grafton, Jean M. Carlson, Peter J. Mucha