• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 25 matches

• 2024
• 
  Nicholas Wymbs, Maxine Major, Ryan Gabrys, Kimberly Ferguson-Walter:
  Physiological Response to Cyber and Psychological Deception. HICSS 2024: 964-973
• 2021
• 
  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)
• 
  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
• 
  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)
• 
  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
• 
  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)
• 
  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)
• 
  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)
• 
  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)
• 
  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)
• 2019
• 
  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)
• 
  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
• 
  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
• 
  Ankit N. Khambhati, Marcelo Gomes Mattar, Nicholas F. Wymbs, Scott T. Grafton, Danielle S. Bassett:
  Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration. NeuroImage 166: 385-399 (2018)
• 
  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)
• 
  Pranav G. Reddy, Marcelo Gomes Mattar, Andrew C. Murphy, Nicholas F. Wymbs, Scott T. Grafton, Theodore D. Satterthwaite, Danielle S. Bassett:
  Brain state flexibility accompanies motor-skill acquisition. NeuroImage 171: 135-147 (2018)
• 
  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
• 2017
• 
  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
• 
  Archana Venkataraman, Nicholas F. Wymbs, Mary Beth Nebel, Stewart Mostofsky:
  A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. CNI@MICCAI 2017: 60-69
• 2016
• 
  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)
• 
  Firas Mawase, Nicholas F. Wymbs, Shintaro Uehara, Pablo Celnik:
  Reward gain model describes cortical use-dependent plasticity. EMBC 2016: 5-8
• 2015
• 
  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
• 
  Alexander V. Mantzaris, Danielle S. Bassett, Nicholas F. Wymbs, Ernesto Estrada, Mason A. Porter, Peter J. Mucha, Scott T. Grafton, Desmond J. Higham:
  Dynamic network centrality summarizes learning in the human brain. J. Complex Networks 1(1): 83-92 (2013)
• 
  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
• 
  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)