Maneesh Sahani

According to our database, Maneesh Sahani authored at least 75 papers between 1997 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Understanding dual process cognition via the minimum description length principle.

Ted Moskovitz, Kevin J. Miller, Maneesh Sahani, Matthew M. Botvinick

PLoS Comput. Biol., 2024

Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset.

Alexandre Galashov, Michalis K. Titsias, András György, Clare Lyle, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani

CoRR, 2024

2023

Prediction under Latent Subgroup Shifts with High-Dimensional Observations.

William I. Walker, Arthur Gretton, Maneesh Sahani

CoRR, 2023

Successor-Predecessor Intrinsic Exploration.

Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J. Gershman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A State Representation for Diminishing Rewards.

Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Minimum Description Length Control.

Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matt M. Botvinick

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised representation learning with recognition-parametrised probabilistic models.

William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Deep learning, reinforcement learning, and world models.

Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto

Neural Networks, 2022

Unsupervised representational learning with recognition-parametrised probabilistic models.

William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani

CoRR, 2022

Amortised Inference in Structured Generative Models with Explaining Away.

Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani

CoRR, 2022

Structured Recognition for Generative Models with Explaining Away.

Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning neural codes for perceptual uncertainty.

Mehrdad Salmasi, Maneesh Sahani

Proceedings of the IEEE International Symposium on Information Theory, 2022

A First-Occupancy Representation for Reinforcement Learning.

Ted Moskovitz, Spencer R. Wilson, Maneesh Sahani

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning.

Grace W. Lindsay, Josh Merel, Tom Mrsic-Flogel, Maneesh Sahani

CoRR, 2021

Probabilistic Tensor Decomposition of Neural Population Spiking Activity.

Hugo Soulat, Sepiedeh Keshavarzi, Troy W. Margrie, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Non-reversible Gaussian processes for identifying latent dynamical structure in neural data.

Virginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Organizing recurrent network dynamics by task-computation to enable continual learning.

Lea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Amortised Learning by Wake-Sleep.

Li K. Wenliang, Theodore H. Moskovitz, Heishiro Kanagawa, Maneesh Sahani

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

A neurally plausible model for online recognition and postdiction in a dynamical environment.

Li Kevin Wenliang, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A neurally plausible model learns successor representations in partially observable environments.

Eszter Vértes, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Kernel Instrumental Variable Regression.

Rahul Singh, Maneesh Sahani, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning interpretable continuous-time models of latent stochastic dynamical systems.

Lea Duncker, Gergo Bohner, Julien Boussard, Maneesh Sahani

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Empirical fixed point bifurcation analysis.

Gergo Bohner, Maneesh Sahani

CoRR, 2018

Flexible and accurate inference and learning for deep generative models.

Eszter Vértes, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Temporal alignment and latent Gaussian process factor inference in population spike trains.

Lea Duncker, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

A Universal Marginalizer for Amortized Inference in Generative Models.

Laura Douglas, Iliyan Zarov, Konstantinos Gourgoulias, Chris Lucas, Chris Hart, Adam Baker, Maneesh Sahani, Yura Perov, Saurabh Johri

CoRR, 2017

Modelling the dynamics of integrating context into perception: in good and in poor readers.

Itay Lieder, Vincent Adam, Maneesh Sahani, Merav Ahissar

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

Score-matching estimators for continuous-time point-process regression models.

Maneesh Sahani, Gergo Bohner, Arne Meyer

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Convolutional higher order matching pursuit.

Gergo Bohner, Maneesh Sahani

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference.

Vincent Adam, James Hensman, Maneesh Sahani

Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

2015

The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction.

Ross S. Williamson, Maneesh Sahani, Jonathan W. Pillow

PLoS Comput. Biol., 2015

Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM).

Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Time-Frequency Analysis as Probabilistic Inference.

Richard E. Turner, Maneesh Sahani

IEEE Trans. Signal Process., 2014

Efficient occlusive components analysis.

Marc Henniges, Richard E. Turner, Maneesh Sahani, Julian Eggert, Jörg Lücke

J. Mach. Learn. Res., 2014

2013

Outlier Responses Reflect Sensitivity to Statistical Structure in the Human Brain.

Marta I. Garrido, Maneesh Sahani, Raymond J. Dolan

PLoS Comput. Biol., 2013

Regularization and nonlinearities for neural language models: when are they needed?

Marius Pachitariu, Maneesh Sahani

CoRR, 2013

Recurrent linear models of simultaneously-recorded neural populations.

Marius Pachitariu, Biljana Petreska, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Extracting regions of interest from biological images with convolutional sparse block coding.

Marius Pachitariu, Adam M. Packer, Noah Pettit, Henry Dalgleish, Michael Häusser, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Learning visual motion in recurrent neural networks.

Marius Pachitariu, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Spectral learning of linear dynamics from generalised-linear observations with application to neural population data.

Lars Buesing, Jakob H. Macke, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Variational Inference in Non-negative Factorial Hidden Markov Models for Efficient Audio Source Separation.

Gautham J. Mysore, Maneesh Sahani

Proceedings of the 29th International Conference on Machine Learning, 2012

Decomposing signals into a sum of amplitude and frequency modulated sinusoids using probabilistic inference.

Richard E. Turner, Maneesh Sahani

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Demodulation as Probabilistic Inference.

Richard E. Turner, Maneesh Sahani

IEEE ACM Trans. Audio Speech Lang. Process., 2011

Probabilistic amplitude and frequency demodulation.

Richard E. Turner, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 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, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Empirical models of spiking in neural populations.

Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Statistical inference for single- and multi-band Probabilistic Amplitude Demodulation.

Richard E. Turner, Maneesh Sahani

Proceedings of the IEEE International Conference on Acoustics, 2010

2009

A Structured Model of Video Reproduces Primary Visual Cortical Organisation.

Pietro Berkes, Richard E. Turner, Maneesh Sahani

PLoS Comput. Biol., 2009

Occlusive Components Analysis.

Jörg Lücke, Richard E. Turner, Maneesh Sahani, Marc Henniges

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Maximal Causes for Non-linear Component Extraction.

Jörg Lücke, Maneesh Sahani

J. Mach. Learn. Res., 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, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Fast Gaussian process methods for point process intensity estimation.

John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Machine Learning, 2008

A factor-analysis decoder for high-performance neural prostheses.

Gopal Santhanam, Byron M. Yu, Vikash Gilja, Stephen I. Ryu, Afsheen Afshar, Maneesh Sahani, Krishna V. Shenoy

Proceedings of the IEEE International Conference on Acoustics, 2008

2007

A Maximum-Likelihood Interpretation for Slow Feature Analysis.

Richard E. Turner, Maneesh Sahani

Neural Comput., 2007

Modeling Natural Sounds with Modulation Cascade Processes.

Richard E. Turner, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes.

John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On Sparsity and Overcompleteness in Image Models.

Pietro Berkes, Richard E. Turner, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Inferring Elapsed Time from Stochastic Neural Processes.

Misha B. Ahrens, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models.

Byron M. Yu, John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Neural Information Processing, 14th International Conference, 2007

Latent Identity Variables: Biometric Matching Without Explicit Identity Estimation.

Simon J. D. Prince, Jania Aghajanian, Umar Mohammed, Maneesh Sahani

Proceedings of the Advances in Biometrics, International Conference, 2007

Generalized Softmax Networks for Non-linear Component Extraction.

Jörg Lücke, Maneesh Sahani

Proceedings of the Artificial Neural Networks, 2007

Probabilistic Amplitude Demodulation.

Richard E. Turner, Maneesh Sahani

Proceedings of the Independent Component Analysis and Signal Separation, 2007

2005

Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction.

Kensuke Sekihara, Maneesh Sahani, Srikantan S. Nagarajan

NeuroImage, 2005

A simple nonparametric statistical thresholding for MEG spatial-filter source reconstruction images.

Kensuke Sekihara, Maneesh Sahani, Srikantan S. Nagarajan

NeuroImage, 2005

Extracting Dynamical Structure Embedded in Neural Activity.

Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2003

Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity.

Maneesh Sahani, Peter Dayan

Neural Comput., 2003

Reconstructing MEG Sources with Unknown Correlations.

Maneesh Sahani, Srikantan S. Nagarajan

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning.

Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002

Evidence Optimization Techniques for Estimating Stimulus-Response Functions.

Maneesh Sahani, Jennifer F. Linden

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

How Linear are Auditory Cortical Responses?.

Maneesh Sahani, Jennifer F. Linden

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Adaptation and Unsupervised Learning.

Peter Dayan, Maneesh Sahani, Gregoire Deback

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2000

Spike train coherence in macaque parietal cortex during a memory saccade task.

John S. Pezaris, Maneesh Sahani, Richard A. Andersen

Neurocomputing, 2000

1999

Simultaneous paired intracellular and tetrode recordings for evaluating the performance of spike sorting algorithms.

Michael Wehr, John S. Pezaris, Maneesh Sahani

Neurocomputing, 1999

Response-locked changes in auto- and cross-covariations in parietal cortex.

John S. Pezaris, Maneesh Sahani, Richard A. Andersen

Neurocomputing, 1999

1997

On the Separation of Signals from Neighboring Cells in Tetrode Recordings.

Maneesh Sahani, John S. Pezaris, Richard A. Andersen

Proceedings of the Advances in Neural Information Processing Systems 10, 1997