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Lucas C. Parra
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2020 – today
- 2024
- [i7]Osvaldo Matías Velarde, Lucas C. Parra, Paolo Boldi, Hernán A. Makse:
The Role of Fibration Symmetries in Geometric Deep Learning. CoRR abs/2408.15894 (2024) - [i6]Aimar Silvan Ortubay, Lucas C. Parra, Jens Madsen:
Real-time estimation of overt attention from dynamic features of the face using deep-learning. CoRR abs/2409.13084 (2024) - 2023
- [j38]Osvaldo Matías Velarde
, Hernán A. Makse, Lucas C. Parra:
Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback. PLoS Comput. Biol. 19(11) (2023) - 2022
- [j37]Yu Huang
Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment. J. Digit. Imaging 35(6): 1662-1672 (2022) - 2020
- [j36]Maximilian Nentwich
Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI. NeuroImage 218: 117001 (2020) - [i5]Lukas Hirsch, Yu Huang, Shaojun Luo, Carolina Rossi Saccarelli, Roberto Lo Gullo, Isaac Daimiel Naranjo, Almir Galvão Vieira Bitencourt, Natsuko Onishi, Eun Sook Ko, Dortis Leithner, Daly Avendano, Sarah Eskreis-Winkler, Mary Hughes, Danny F. Martinez, Katja Pinker, Krishna Juluru, Amin E. El-Rowmeim, Pierre Elnajjar, Hedvig Hricak, Elizabeth A. Morris, Hernán A. Makse, Lucas C. Parra, Elizabeth J. Sutton:
Deep learning achieves radiologist-level performance of tumor segmentation in breast MRI. CoRR abs/2009.09827 (2020)
2010 – 2019
- 2019
- [j35]Nigel Gebodh
Inherent physiological artifacts in EEG during tDCS. NeuroImage 185: 408-424 (2019) - [j34]Alain de Cheveigné, Giovanni M. Di Liberto
Multiway canonical correlation analysis of brain data. NeuroImage 186: 728-740 (2019) - [i4]Lukas Hirsch, Yu Huang, Lucas C. Parra:
Tissue segmentation with deep 3D networks and spatial priors. CoRR abs/1905.10010 (2019) - 2018
- [j33]Stefan Haufe
Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus. NeuroImage 179: 79-91 (2018) - [j32]Jacek P. Dmochowski, Jason J. Ki, Paul DeGuzman, Paul Sajda, Lucas C. Parra:
Extracting multidimensional stimulus-response correlations using hybrid encoding-decoding of neural activity. NeuroImage 180(Part): 134-146 (2018) - [c24]Yu Huang, Abhishek Datta
ROAST: An Open-Source, Fully-Automated, Realistic Volumetric-Approach-Based Simulator For TES. EMBC 2018: 3072-3075 - [c23]Yu Huang, Chris Thomas, Abhishek Datta, Lucas C. Parra:
Optimized tDCS for Targeting Multiple Brain Regions: An Integrated Implementation. EMBC 2018: 3545-3548 - [i3]Lucas C. Parra, Stefan Haufe, Jacek P. Dmochowski:
Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data. CoRR abs/1801.08881 (2018) - 2017
- [j31]Jacek P. Dmochowski, Laurent Koessler
Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation. NeuroImage 157: 69-80 (2017) - 2016
- [j30]Yu Huang
The New York Head - A precise standardized volume conductor model for EEG source localization and tES targeting. NeuroImage 140: 150-162 (2016) - [i2]Andreas Trier Poulsen, Simon Kamronn, Jacek Dmochowski, Lucas C. Parra, Lars Kai Hansen:
Measuring engagement in a classroom: Synchronised neural recordings during a video presentation. CoRR abs/1604.03019 (2016) - 2015
- [j29]Martín Graziano
Neural Correlates of Perceived Confidence in a Partial Report Paradigm. J. Cogn. Neurosci. 27(6): 1090-1103 (2015) - 2014
- [j28]Daniel Rosenthal, Paul DeGuzman, Lucas C. Parra, Paul Sajda:
Evoked Neural Responses to Events in Video. IEEE J. Sel. Top. Signal Process. 8(3): 358-365 (2014) - [j27]Andrea Antal, Marom Bikson, Abhishek Datta
Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain. NeuroImage 85: 1040-1047 (2014) - [j26]Alain de Cheveigné
Joint decorrelation, a versatile tool for multichannel data analysis. NeuroImage 98: 487-505 (2014) - [c22]Andreas Trier Poulsen, Simon Kamronn, Lucas C. Parra, Lars Kai Hansen
Bayesian correlated component analysis for inference of joint EEG activation. PRNI 2014: 1-4 - 2013
- [j25]Justin K. Rice, Christopher Rorden
Subject position affects EEG magnitudes. NeuroImage 64: 476-484 (2013) - [j24]Jacek P. Dmochowski, Abhishek Datta
Targeted transcranial direct current stimulation for rehabilitation after stroke. NeuroImage 75: 12-19 (2013) - [j23]Davide Reato
Transcranial Electrical Stimulation Accelerates Human Sleep Homeostasis. PLoS Comput. Biol. 9(2) (2013) - [c21]Lucas C. Parra, Jacek P. Dmochovski, Joao Dias, Alain de Cheveigné:
Spatial projections of neural arrays: A short guide to classic and new signal analysis techniques. BCI 2013: 10-11 - [i1]Lev Muchnik, Sen Pei, Lucas C. Parra, Saulo D. S. Reis, José S. Andrade Jr., Shlomo Havlin, Hernán A. Makse:
Origins of power-law degree distribution in the heterogeneity of human activity in social networks. CoRR abs/1304.4523 (2013) - 2012
- [j22]Davide Reato
Computational model of neuron-astrocyte interactions during focal seizure generation. Frontiers Comput. Neurosci. 6: 81 (2012) - [c20]Egas M. Caparelli-Daquer
A pilot study on effects of 4×1 High-Definition tDCS on motor cortex excitability. EMBC 2012: 735-738 - [c19]Yu Huang
An automated method for high-definition transcranial direct current stimulation modeling. EMBC 2012: 5376-5379 - [c18]Jacek P. Dmochowski, Marom Bikson, Abhishek Datta
On the role of electric field orientation in optimal design of transcranial current stimulation. EMBC 2012: 6426-6429 - [c17]Janne Mathias Hahne, Hubertus Rehbaum, Felix Bießmann, Frank C. Meinecke, Klaus-Robert Müller
Simultaneous and proportional control of 2D wrist movements with myoelectric signals. MLSP 2012: 1-6 - 2010
- [j21]Christoforos Christoforou, Robert M. Haralick, Paul Sajda, Lucas C. Parra:
Second-Order Bilinear Discriminant Analysis. J. Mach. Learn. Res. 11: 665-685 (2010) - [j20]Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra:
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds. J. Mach. Learn. Res. 11: 3313-3332 (2010) - [j19]Paul Sajda, Eric Pohlmeyer, Jun Wang, Lucas C. Parra, Christoforos Christoforou
In a Blink of an Eye and a Switch of a Transistor: Cortically Coupled Computer Vision. Proc. IEEE 98(3): 462-478 (2010) - [p1]Paul Sajda, Eric Pohlmeyer, Jun Wang, Barbara Hanna, Lucas C. Parra, Shih-Fu Chang:
Cortically-Coupled Computer Vision. Brain-Computer Interfaces 2010: 133-148
2000 – 2009
- 2009
- [j18]Lucas C. Parra, Jeffrey M. Beck, Anthony J. Bell:
On the Maximization of Information Flow Between Spiking Neurons. Neural Comput. 21(11): 2991-3009 (2009) - 2008
- [j17]Lucas C. Parra, Christoforos Christoforou
Spatiotemporal Linear Decoding of Brain State. IEEE Signal Process. Mag. 25(1): 107-115 (2008) - [c16]Jonathan Le Roux, Alain de Cheveigné, Lucas C. Parra:
Adaptive Template Matching with Shift-Invariant Semi-NMF. NIPS 2008: 921-928 - 2007
- [j16]Mads Dyrholm, Christoforos Christoforou, Lucas C. Parra:
Bilinear Discriminant Component Analysis. J. Mach. Learn. Res. 8: 1097-1111 (2007) - [c15]Christoforos Christoforou, Paul Sajda, Lucas C. Parra:
Second Order Bilinear Discriminant Analysis for single trial EEG analysis. NIPS 2007: 313-320 - 2006
- [j15]Clay Spence, Lucas C. Parra, Paul Sajda:
Varying complexity in tree-structured image distribution models. IEEE Trans. Image Process. 15(2): 319-330 (2006) - [c14]Mads Dyrholm, Lucas C. Parra:
Smooth bilinear classification of EEG. EMBC 2006: 4249-4252 - [c13]Thomas Radman, Lucas C. Parra, Marom Bikson:
Amplification of small electric fields by neurons; implications for spike timing. EMBC 2006: 4949-4952 - [c12]Akaysha C. Tang, Matthew T. Sutherland
Classifying Single-Trial ERPs from Visual and Frontal Cortex during Free Viewing. IJCNN 2006: 1376-1383 - 2005
- [j14]Lucas C. Parra, Clay D. Spence, Adam D. Gerson, Paul Sajda:
Recipes for the linear analysis of EEG. NeuroImage 28(2): 326-341 (2005) - [j13]Adam D. Gerson, Lucas C. Parra, Paul Sajda:
Cortical origins of response time variability during rapid discrimination of visual objects. NeuroImage 28(2): 342-353 (2005) - 2004
- [j12]Paul Sajda, Shuyan Du, Truman R. Brown, Radka Stoyanova, Dikoma C. Shungu
Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain. IEEE Trans. Medical Imaging 23(12): 1453-1465 (2004) - [c11]Anthony J. Bell, Lucas C. Parra:
Maximising Sensitivity in a Spiking Network. NIPS 2004: 121-128 - 2003
- [j11]Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter
Single-trial detection in EEG and MEG: Keeping it linear. Neurocomputing 52-54: 177-183 (2003) - [j10]Lucas C. Parra, Paul Sajda:
Blind Source Separation via Generalized Eigenvalue Decomposition. J. Mach. Learn. Res. 4: 1261-1269 (2003) - [j9]Paul Sajda, Clay Spence, Lucas C. Parra:
A multi-scale probabilistic network model for detection, synthesis and compression in mammographic image analysis. Medical Image Anal. 7(2): 187-204 (2003) - 2002
- [j8]Lucas C. Parra, Christopher V. Alvino, Akaysha C. Tang, Barak A. Pearlmutter
Linear Spatial Integration for Single-Trial Detection in Encephalography. NeuroImage 17(1): 223-230 (2002) - [j7]Lucas C. Parra, Christopher V. Alvino:
Geometric source separation: merging convolutive source separation with geometric beamforming. IEEE Trans. Speech Audio Process. 10(6): 352-362 (2002) - [c10]Paul Sajda, Clay Spence, Lucas C. Parra:
Capturing contextual dependencies in medical imagery using hierarchical multi-scale models. ISBI 2002: 165-168 - 2000
- [j6]Lucas C. Parra, Clay Spence:
Convolutive blind separation of non-stationary sources. IEEE Trans. Speech Audio Process. 8(3): 320-327 (2000) - [j5]Lucas C. Parra, Clay Spence:
On-line Convolutive Blind Source Separation of Non-Stationary Signals. J. VLSI Signal Process. 26(1-2): 39-46 (2000) - [c9]Paul Sajda, Clay Spence, Lucas C. Parra, Robert M. Nishikawa
Hierarchical, Multi-resolution Models for Object Recognition: Applications to Mammographic Computer-aided Diagnosis. AIPR 2000: 159-165 - [c8]Clay Spence, Lucas C. Parra, Paul Sajda:
Hierarchical Image Probability (HIP) Models. ICIP 2000: 320-323 - [c7]Clay D. Spence, Lucas C. Parra, Paul Sajda:
Mammographic mass detection with a hierarchical image probability (HIP) model. Medical Imaging: Image Processing 2000 - [c6]Lucas C. Parra, Clay Spence, Paul Sajda:
Higher-Order Statistical Properties Arising from the Non-Stationarity of Natural Signals. NIPS 2000: 786-792
1990 – 1999
- 1999
- [c5]Clay Spence, Lucas C. Parra:
Hierarchical Image Probability (H1P) Models. NIPS 1999: 848-854 - [c4]Lucas C. Parra, Clay Spence, Paul Sajda, Andreas Ziehe, Klaus-Robert Müller:
Unmixing Hyperspectral Data. NIPS 1999: 942-948 - 1998
- [j4]Lucas C. Parra, Harrison H. Barrett:
List-Mode Likelihood EM Algorithm and Noise Estimation Demonstrated on 2D-PET. IEEE Trans. Medical Imaging 17(2): 228-235 (1998) - 1997
- [j3]Gustavo Deco, Lucas C. Parra:
Non-linear Feature Extraction by Redundancy Reduction in an Unsupervised Stochastic Neural Network. Neural Networks 10(4): 683-691 (1997) - [c3]Lucas C. Parra:
Temporal Models in Blind Source Separation. Summer School on Neural Networks 1997: 229-247 - 1996
- [j2]Lucas C. Parra, Gustavo Deco, Stefan Miesbach:
Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps. Neural Comput. 8(2): 260-269 (1996) - [c2]Barak A. Pearlmutter, Lucas C. Parra:
Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA. NIPS 1996: 613-619 - 1995
- [b1]Lucas C. Parra:
Unüberwachtes Lernen mit informationstheoretischen Kriterien in konnektionistischen Modellen. Ludwig Maximilian University of Munich, Germany, 1995, pp. 1-132 - [j1]Lucas C. Parra, Gustavo Deco:
Continuous Boltzmann machine with rotor neurons. Neural Networks 8(3): 375-385 (1995) - [c1]Lucas C. Parra:
Symplectic Nonlinear Component Analysis. NIPS 1995: 437-443
Coauthor Index
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last updated on 2024-10-18 19:28 CEST by the dblp team
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