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Jason A. Palmer
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2020 – today
- 2023
- [c14]Gwenevere Frank, Seyed Yahya Shirazi, Jason A. Palmer, Gert Cauwenberghs, Scott Makeig, Arnaud Delorme:
An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA. BIBE 2023: 205-210
2010 – 2019
- 2018
- [j2]Sheng-Hsiou Hsu
, Luca Pion-Tonachini, Jason A. Palmer, Makoto Miyakoshi
Modeling brain dynamic state changes with adaptive mixture independent component analysis. NeuroImage 183: 47-61 (2018) - 2013
- [c13]Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Makeig:
The linear process mixture model. MLSP 2013: 1-6 - 2012
- [c12]Jason A. Palmer, Scott Makeig:
Contrast Functions for Independent Subspace Analysis. LVA/ICA 2012: 115-122 - 2011
- [c11]Zeynep Akalin Acar, Jason A. Palmer, Gregory A. Worrell, Scott Makeig:
Electrocortical source imaging of intracranial EEG data in epilepsy. EMBC 2011: 3909-3912 - 2010
- [c10]Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Makeig:
Strong Sub- and Super-Gaussianity. LVA/ICA 2010: 303-310
2000 – 2009
- 2009
- [c9]Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delgado:
A complex cross-spectral distribution model using Normal Variance Mean Mixtures. ICASSP 2009: 3569-3572 - [c8]Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Makeig:
Probabilistic Formulation of Independent Vector Analysis Using Complex Gaussian Scale Mixtures. ICA 2009: 90-97 - 2008
- [c7]Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delgado, Bhaskar D. Rao:
Newton method for the ICA mixture model. ICASSP 2008: 1805-1808 - 2007
- [c6]Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D. Rao, Scott Makeig:
Modeling and Estimation of Dependent Subspaces with Non-radially Symmetric and Skewed Densities. ICA 2007: 97-104 - [c5]David P. Wipf
Performance Evaluation of Latent Variable Models with Sparse Priors. ICASSP (2) 2007: 453-456 - 2006
- [c4]Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Makeig:
Super-Gaussian Mixture Source Model for ICA. ICA 2006: 854-861 - [c3]David P. Wipf, Rey Ramírez, Jason A. Palmer, Scott Makeig, Bhaskar D. Rao:
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization. NIPS 2006: 1505-1512 - 2005
- [c2]Jason A. Palmer, David P. Wipf, Kenneth Kreutz-Delgado, Bhaskar D. Rao:
Variational EM Algorithms for Non-Gaussian Latent Variable Models. NIPS 2005: 1059-1066 - 2003
- [j1]Bhaskar D. Rao, Kjersti Engan
Subset selection in noise based on diversity measure minimization. IEEE Trans. Signal Process. 51(3): 760-770 (2003) - [c1]David P. Wipf, Jason A. Palmer, Bhaskar D. Rao:
Perspectives on Sparse Bayesian Learning. NIPS 2003: 249-256
Coauthor Index
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