EPrints submitted by Maneesh Sahani

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Number of EPrints submitted by this user: 19

Factor-analysis methods for higher-performance neural prostheses.
Gopal Santhanam, Byron M. Yu, Vikash Gilja, Stephen I. Ryu, Afsheen Afshar, Maneesh Sahani and Krishna V. Shenoy
Journal of Neurophysiology 2009.

Neural decoding of movements: From linear to nonlinear trajectory models.
Byron M Yu, John P Cunningham, Krishna V Shenoy and Maneesh Sahani
In: Neural Information Processing – ICONIP 2007, Proceedings, Part I (2008) Springer , pp. 586-595.

Modeling natural sounds with modulation cascade processes.
Richard Turner and Maneesh Sahani
In: Advances in Neural Information Processing Systems (2008) MIT Press , Cambridge, USA .

A factor-analysis decoder for high-performance neural prostheses.
Gopal Santhanam, Byron M. Yu, Vikash Gilja, Stephen I. Ryu, Afsheen Afshar, Maneesh Sahani and Krishna V. Shenoy
In: ICASSP’08: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (2008) IEEE , pp. 5208-5211.

Maximal causes for non-linear component extraction.
Jörg Lücke and Maneesh Sahani
Journal of Machine Learning Research Volume 9, pp. 1227-1267, 2008.

Fast Gaussian process methods for point process intensity estimation.
John P Cunningham, Krishna V Shenoy and Maneesh Sahani
In: ICML ’08: Proceedings of the 25th international conference on Machine learning (2008) Omni Press , Helsinki, Finland , pp. 192-199.

Inferring neural firing rates from spike trains using Gaussian processes.
John P Cunningham, Byron M Yu, Krishna V Shenoy and Maneesh Sahani
In: Advances in Neural Information Processing Systems (2008) MIT Press , Cambridge, USA .

On sparsity and overcompleteness in image models.
Pietro Berkes, Richard Turner and Maneesh Sahani
In: Advances in Neural Information Processing Systems (2008) MIT Press , Cambridge, USA .

Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.
Byron M Yu, John P Cunningham, Gopal Santhanam, Stephen I Ryu, Krishna V Shenoy and Maneesh Sahani
In: Advances in Neural Information Processing Systems (2009) MIT Press , Cambridge, USA .

Inferring elapsed time from stochastic neural processes
Misha Ahrens and Maneesh Sahani
Advances in Neural Information Processing Systems Volume 20, 2008.

A structured model of video reproduces primary visual cortical organisation
Pietro Berkes, Richard Turner and Maneesh Sahani
PLoS Computational Biology Volume 5, Number 9, e1000495, 2009.

Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity.
Byron M Yu, John P Cunningham, Gopal Santhanam, Stephen I Ryu, Krishna V Shenoy and Maneesh Sahani
Journal of Neurophysiology Volume 102, pp. 614-635, 2009.

Occlusive components analysis
J Lücke, Richard Turner, Maneesh Sahani and M Henniges
In: Advances in Neural Information Processing Systems (2009) Curran Associates, Inc. .

Neural decoding for motor and communication prostheses
Byron M Yu, Gopal Santhanam, Maneesh Sahani and Krishna V Shenoy
In: Statistical Signal Processing for Neuroscience (2010) Elsevier , pp. 219-263.

Statistical inference for single- and multi-band probabilistic amplitude demodulation
Richard Turner and Maneesh Sahani
In: ICASSP’10: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (2010) IEEE .

Two problems with variational expectation maximisation for time-series models
Richard Turner and Maneesh Sahani
In: Inference and Learning in Dynamic Models (2011) Cambridge University Press .

Modelling cue integration in clutter
Maneesh Sahani and Louise Whiteley
In: Sensory Cue Integration (2011) Oxford University Press .

Observers exploit stochastic models of sensory change to help judge the passage of time
Misha Ahrens and Maneesh Sahani
Current Biology Volume 21, Number 3, pp. 200-206, 2011.

Demodulation as Probabilistic Inference
Richard Turner and Maneesh Sahani
IEEE Transactions on Audio, Speech and Language Processing 2011.