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All publications by Maneesh Sahani
authors venues years



Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing and Maneesh Sahani
Advances in Neural Information Processing Systems 28, 2015


Extracting regions of interest from biological images with convolutional sparse block coding
Marius Pachitariu, Adam M. Packer, Noah Pettit, Henry Dalgleish, Michael Hausser and Maneesh Sahani
Advances in Neural Information Processing Systems 26, 2013


Recurrent linear models of simultaneously-recorded neural populations
Marius Pachitariu, Biljana Petreska and Maneesh Sahani
Advances in Neural Information Processing Systems 26, 2013


Spectral learning of linear dynamics from generalised-linear observations with application to neural population data
Lars Buesing, Maneesh Sahani and Jakob H. Macke
Advances in Neural Information Processing Systems 25, 2012


Learning visual motion in recurrent neural networks
Marius Pachitariu and Maneesh Sahani
Advances in Neural Information Processing Systems 25, 2012


Variational Inference in Non-negative Factorial Hidden Markov Models for Efficient Audio Source Separation
Gautham Mysore and Maneesh Sahani
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Empirical models of spiking in neural populations
Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy and Maneesh Sahani
Advances in Neural Information Processing Systems 24, 2011


Probabilistic amplitude and frequency demodulation
Richard Turner and Maneesh Sahani
Advances in Neural Information Processing Systems 24, 2011


Dynamical segmentation of single trials from population neural data
Biljana Petreska, Byron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy and Maneesh Sahani
Advances in Neural Information Processing Systems 24, 2011


Occlusive Components Analysis
Jörg Lücke, Richard Turner, Maneesh Sahani and Marc Henniges
Advances in Neural Information Processing Systems 22, 2009


Maximal Causes for Non-linear Component Extraction
Jörg Lücke and Maneesh Sahani
Journal of Machine Learning Research, 2008


Fast Gaussian process methods for point process intensity estimation
John P. Cunningham, Krishna V. Shenoy and Maneesh Sahani
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


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
Advances in Neural Information Processing Systems 21, 2008


Modeling Natural Sounds with Modulation Cascade Processes
Richard Turner and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


Inferring Elapsed Time from Stochastic Neural Processes
Misha Ahrens and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


On Sparsity and Overcompleteness in Image Models
Pietro Berkes, Richard Turner and Maneesh Sahani
Advances in Neural Information Processing Systems 20, 2007


A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning
Maneesh Sahani
Advances in Neural Information Processing Systems 16, 2003


Reconstructing MEG Sources with Unknown Correlations
Maneesh Sahani and Srikantan S. Nagarajan
Advances in Neural Information Processing Systems 16, 2003


Evidence Optimization Techniques for Estimating Stimulus-Response Functions
Maneesh Sahani and Jennifer F. Linden
Advances in Neural Information Processing Systems 15, 2002


Adaptation and Unsupervised Learning
Peter Dayan, Maneesh Sahani and Gregoire Deback
Advances in Neural Information Processing Systems 15, 2002


How Linear are Auditory Cortical Responses?
Maneesh Sahani and Jennifer F. Linden
Advances in Neural Information Processing Systems 15, 2002