James R. Williamson

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Thomas QuatieriMITVerified email at ll.mit.edu
Brian S. HelferAssociate Staff in Bioengineering Systems and Technologies, MIT Lincoln LaboratoryVerified email at ll.mit.edu
Daryush D. Mehta, PhDDirector of Voice Science and Technology Laboratory, Center for Laryngeal Surgery and VoiceVerified email at alum.mit.edu
Gregory CiccarelliApplied Scientist, AmazonVerified email at mit.edu
Stephen GrossbergWang Professor of Cognitive and Neural Systems, Boston UniversityVerified email at bu.edu
Adam LammertAssistant Professor, Mathematics & Computer Science, College of the Holy CrossVerified email at holycross.edu
Bea YuAVP, Artificial IntelligenceVerified email at voya.com
Christopher SmaltMIT Lincoln Laboratory; Human Health & Performance Systems GroupVerified email at mit.edu
Daniel W. BlissProfessor, Electrical, Computer, and Energy Engineering, Director WISCA, Arizona State UniversityVerified email at asu.edu
Rachelle Horwitz-MartinVerified email at mit.edu
Isao HayashiKansai UniversityVerified email at kansai-u.ac.jp
Tejash PatelMIT Lincoln LabsVerified email at ll.mit.edu
James MundtSand Ridge Secure Treatment CenterVerified email at dhs.wisconsin.gov
Buller, mjBrown University / USARIEMVerified email at brown.edu
Ennio MingollaNortheastern University, Department of Communication Sciences and DisordersVerified email at neu.edu
David PaydarfarDell Medical School, The University of Texas at AustinVerified email at austin.utexas.edu
Pooya KhorramiMIT Lincoln LaboratoryVerified email at ll.mit.edu
Youngjune GwonExecutive Vice President, Samsung SDSVerified email at samsung.com
Miriam ChaMIT Lincoln Laboratory, Harvard UniversityVerified email at g.harvard.edu
H. T. KungProfessor, Harvard UniversityVerified email at harvard.edu

James R. Williamson

Technical Staff in Human Health & Performance Systems, Lincoln Laboratory

Verified email at ll.mit.edu

biomedical prediction signal processing machine learning cortical processing


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Gaussian ARTMAP: A neural network for fast incremental learning of noisy multidimensional maps JR Williamson Neural networks 9 (5), 881-897, 1996	440	1996
Seizure prediction using EEG spatiotemporal correlation structure JR Williamson, DW Bliss, DW Browne, JT Narayanan Epilepsy & behavior 25 (2), 230-238, 2012	255	2012
Detecting Depression using Vocal, Facial and Semantic Communication Cues JR Williamson, E Godoy, M Cha, A Schwarzentruber, P Khorrami, Y Gwon, ... AVEC '16 Proceedings of the 6th International Workshop on Audio/Visual …, 2016	247	2016
Vocal and facial biomarkers of depression based on motor incoordination and timing JR Williamson, TF Quatieri, BS Helfer, G Ciccarelli, DD Mehta Proceedings of the 4th international workshop on audio/visual emotion …, 2014	247	2014
A neural model of how horizontal and interlaminar connections of visual cortex develop into adult circuits that carry out perceptual grouping and learning S Grossberg, JR Williamson Cerebral cortex 11 (1), 37-58, 2001	244	2001
Vocal biomarkers of depression based on motor incoordination JR Williamson, TF Quatieri, BS Helfer, R Horwitz, B Yu, DD Mehta Proceedings of the 3rd ACM international workshop on Audio/visual emotion …, 2013	238	2013
Synthetic aperture radar processing by a multiple scale neural system for boundary and surface representation S Grossberg, E Mingolla, J Williamson Neural Networks 8 (7-8), 1005-1028, 1995	159	1995
On the relative importance of vocal source, system, and prosody in human depression R Horwitz, TF Quatieri, BS Helfer, B Yu, JR Williamson, J Mundt 2013 IEEE international conference on body sensor networks, 1-6, 2013	83	2013
Tracking depression severity from audio and video based on speech articulatory coordination JR Williamson, D Young, AA Nierenberg, J Niemi, BS Helfer, TF Quatieri Computer Speech & Language 55, 40-56, 2019	82	2019
Classification of depression state based on articulatory precision. BS Helfer, TF Quatieri, JR Williamson, DD Mehta, R Horwitz, B Yu Interspeech, 2172-2176, 2013	74	2013
Epileptic seizure prediction using the spatiotemporal correlation structure of intracranial EEG JR Williamson, DW Bliss, DW Browne 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011	62	2011
A constructive, incremental-learning network for mixture modeling and classification JR Williamson Neural Computation 9 (7), 1517-1543, 1997	59	1997
A self-organizing neural system for learning to recognize textured scenes S Grossberg, JR Williamson Vision Research 39 (7), 1385-1406, 1999	57	1999
A Gaussian adaptive resonance theory neural network classification algorithm applied to supervised land cover mapping using multitemporal vegetation index data D Muchoney, J Williamson IEEE transactions on Geoscience and Remote Sensing 39 (9), 1969-1977, 2001	52	2001
Segment-dependent dynamics in predicting parkinson's disease. JR Williamson, TF Quatieri, BS Helfer, J Perricone, SS Ghosh, ... Interspeech, 518-522, 2015	51	2015
Generalized two-stage rank regression framework for depression score prediction from speech N Cummins, V Sethu, J Epps, JR Williamson, TF Quatieri, J Krajewski IEEE Transactions on Affective Computing 11 (2), 272-283, 2017	47	2017
Cognitive impairment prediction in the elderly based on vocal biomarkers. B Yu, TF Quatieri, JR Williamson, JC Mundt INTERSPEECH, 3734-3738, 2015	46	2015
Assessment of speech and fine motor coordination in children with autism spectrum disorder T Talkar, JR Williamson, DJ Hannon, HM Rao, S Yuditskaya, KT Claypool, ... IEEe Access 8, 127535-127545, 2020	44	2020
Self-organization of topographic mixture networks using attentional feedback JR Williamson Neural Computation 13 (3), 563-593, 2001	39	2001
Domain adaptation for enhancing speech-based depression detection in natural environmental conditions using dilated CNNs Z Huang, J Epps, D Joachim, B Stasak, JR Williamson, TF Quatieri Interspeech 2020 2020, 4561-4565, 2020	37	2020

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