H. Attias

发表

Hagai Attias, H. Attias, 1999, Neural Computation.

A multimodal variational approach to learning and inference in switching state space models [speech processing application]

Paul W. Fieguth, Li Deng, Hagai Attias, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

A Variational Bayesian Framework for Graphical Models

Hagai Attias, H. Attias, H. Attias, 1999 .

Planning by Probabilistic Inference

Hagai Attias, H. Attias, 2003, AISTATS.

Inferring Parameters and Structure of Latent Variable Models by Variational Bayes

Hagai Attias, H. Attias, 1999, UAI.

Independent Component Analysis: ICA, graphical models and variational methods

H. Attias, 2001 .

Blind Source Separation Exploiting Higher-Order Frequency Dependencies

Te-Won Lee, Soo-Young Lee, Hagai Attias, 2007, IEEE Transactions on Audio, Speech, and Language Processing.

Blind Source Separation and Deconvolution: The Dynamic Component Analysis Algorithm

Hagai Attias, Christoph E. Schreiner, H. Attias, 1998, Neural Computation.

Adaptive Kalman Filtering and Smoothing for Tracking Vocal Tract Resonances Using a Continuous-Valued Hidden Dynamic Model

Li Deng, Alex Acero, Hagai Attias, 2007, IEEE Transactions on Audio, Speech, and Language Processing.

EM algorithms for independent component analysis

H. Attias, 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).

Independent Factor Analysis 1 Statistical Modeling and Blind Source Separation

H. Attias, H Attias, 1999 .

Estimating Causality Measures from Reconstructed Source Time Courses When Large Background Activities Exist

H. Attias, S. Nagarajan, K. Sekihara, 2010 .

Algebraic rotating-frame approach to nuclear reactions

H. Attias, Y. Alhassid, Y. Alhassid, 1994 .

INTERSPEECH 2006-ICSLP hone Array Source Separation using urce Models

H. Attias, 2006 .

Dynamic component analysis of auditory evoked neuromagnetic fields

David Poeppel, H. Attias, H. A. Rowley, 1997 .

Learning parameters and structure of latent variable models by variation Bayes

H. Attias, H. Attias, 1999 .

The Perturbed static path approximation at finite temperature: Observables and strength functions

H. Attias, Y. Alhassid, 1997, nucl-th/9707037.

A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity

Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan, 2006, NeuroImage.

A Spatiotemporal Framework for Estimating Trial-to-Trial Amplitude Variation in Event-Related MEG/EEG

Hagai Attias, Srikantan S. Nagarajan, Barry D. Van Veen, 2009, IEEE Transactions on Biomedical Engineering.

Linear Dynamical System Response Modeling of Trial-to-Trial Amplitude Variability in Event-Related MEG/EEG

H. Attias, S. Nagarajan, B. V. Van Veen, 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

An Expectation–Maximization Method for Spatio–Temporal Blind Source Separation Using an AR-MOG Source Model

Hagai Attias, Srikantan S. Nagarajan, Kenneth E. Hild, 2008, IEEE Transactions on Neural Networks.

Blind source separation and deconvolution by dynamic component analysis

H. Attias, C. E. Schreiner, H. Attias, 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.

Fetal cardiac signal extraction from magnetocardiographic data using a probabilistic algorithm

Hagai Attias, Srikantan S. Nagarajan, Kenneth E. Hild, 2007, Signal Process..

An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality

Lars Kai Hansen, Arkadiusz Stopczynski, Hagai Attias, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data

Julia P. Owen, David P. Wipf, Hagai Attias, 2012, NeuroImage.

Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG

Julia P. Owen, David P. Wipf, Hagai Attias, 2010, NeuroImage.

Probabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data

Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan, 2008, NeuroImage.

A probabilistic algorithm integrating source localization and noise suppression for MEG and EEG data

Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan, 2006, NeuroImage.

A Graphical Model for Audiovisual Object Tracking

Nebojsa Jojic, Hagai Attias, Matthew J. Beal, 2003, IEEE Trans. Pattern Anal. Mach. Intell..

Probabilistic Algorithm for Electromagnetic Brain Imaging with Spatio-Temporal and Forward Model Priors

Srikantan S. Nagarajan, Carsten Stahlhut, L. K. Hansen, 2010 .

Temporal Low-Order Statistics of Natural Sounds

Hagai Attias, Christoph E. Schreiner, H. Attias, 1996, NIPS.

Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity

Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan, 2005, NIPS.

M/EEG imaging by learning mean norms in brain tiles

Hagai Attias, H. Attias, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Evaluating an empirical Bayesian source estimation method with dense array EEG and a realistic head model

D. Tucker, H. T. Attias, J. Song, 2011 .

New EM algorithms for source separation and deconvolution with a microphone array

Hagai Attias, H. Attias, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

Variational inference and learning for segmental switching state space models of hidden speech dynamics

Li Deng, Hagai Attias, Leo J. Lee, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

A Real-Time Magnetoencephalography Brain-Computer Interface Using Interactive 3D Visualization and the Hadoop Ecosystem

Andy Haas, Srikantan S. Nagarajan, Yusuf Ozbek, 2015, Brain sciences.

Audio-visual graphical models for speech processing

Nebojsa Jojic, John R. Hershey, Hagai Attias, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Evaluation of AC-coupled silicon microstrip detectors and Berkeley SVXD readout with 227 GeV/c pions

H. Attias, P. Skubic, E. McCliment, 1991 .

Beam Tests Of Silicon Microstrip Detectors With VLSI Readout

H. Attias, E. McCliment, P. Karchin, 1990, 1990 IEEE Nuclear Science Symposium Conference Record.

A structured speech model with continuous hidden dynamics and prediction-residual training for tracking vocal tract resonances

Li Deng, Alex Acero, Hagai Attias, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Topic regression multi-modal Latent Dirichlet Allocation for image annotation

Hagai Attias, Srikantan S. Nagarajan, Duangmanee Putthividhya, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

An EM Method for Spatio-temporal Blind Source Separation Using an AR-MOG Source Model

Hagai Attias, Srikantan S. Nagarajan, Kenneth E. Hild, 2006, ICA.

Effectiveness of sparse Bayesian algorithm for MVAR coefficient estimation in MEG/EEG source-space causality analysis

Julia P. Owen, Hagai Attias, Kensuke Sekihara, 2011, 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism.

Single microphone source separation using high resolution signal reconstruction

John R. Hershey, Hagai Attias, Trausti T. Kristjansson, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Speech Denoising and Dereverberation Using Probabilistic Models

Li Deng, Alex Acero, John C. Platt, 2000, NIPS.

Supervised topic model for automatic image annotation

Hagai Attias, Srikantan S. Nagarajan, Duangmanee Putthividhya, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

Audio-Video Sensor Fusion with Probabilistic Graphical Models

Nebojsa Jojic, Hagai Attias, Matthew J. Beal, 2002, ECCV.

Stereo Based 3D Tracking and Scene Learning, Employing Particle Filtering within EM

John R. Hershey, Hagai Attias, Trausti T. Kristjansson, 2004, ECCV.

Independent Factor Analysis with Temporally Structured Sources

Hagai Attias, H. Attias, 1999, NIPS.

Coding of Naturalistic Stimuli by Auditory Midbrain Neurons

Hagai Attias, Christoph E. Schreiner, H. Attias, 1997, NIPS.

Source Separation with a Sensor Array Using Graphical Models and Subband Filtering

Hagai Attias, H. Attias, 2002, NIPS.

A hierarchical Bayesian M/EEG imagingmethod correcting for incomplete spatio-temporal priors

Lars Kai Hansen, David P. Wipf, Hagai Attias, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

Lars Kai Hansen, Srikantan S. Nagarajan, Carsten Stahlhut, 2012, NIPS 2012.

A probabilistic algorithm for robust interference suppression in bioelectromagnetic sensor data

Kensuke Sekihara, Srikantan S Nagarajan, Hagai T Attias, 2007, Statistics in medicine.

Author ' s personal copy Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M / EEG data

H. Attias, D. Wipf, S. Nagarajan, 2012 .