Sahani, Maneesh

48 publications

ICLR 2025 Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA Changmin Yu, Maneesh Sahani, Máté Lengyel

NeurIPS 2025 MyoChallenge 2024: A New Benchmark for Physiological Dexterity and Agility in Bionic Humans Cheryl Wang, Chun Kwang Tan, Balint K Hodossy, Shirui Lyu, Pierre Schumacher, James Heald, Kai Biegun, Samo Hromadka, Maneesh Sahani, Gunwoo Park, Beomsoo Shin, JongHyun Park, Seungbum Koo, Chenhui Zuo, Chengtian Ma, Yanan Sui, Nicklas Hansen, Stone Tao, Yuan Gao, Hao Su, Seungmoon Song, Letizia Gionfrida, Massimo Sartori, Guillaume Durandau, Vikash Kumar, Vittorio Caggiano

ICMLW 2024 Modelling Latent Dynamical Systems with Recognition-Parametrised Models Samo Hromadka, Maneesh Sahani

NeurIPS 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

NeurIPS 2023 A State Representation for Diminishing Rewards Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani

ICLR 2023 Minimum Description Length Control Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew Botvinick

ICMLW 2023 Prediction Under Latent Subgroup Shifts with High-Dimensional Observations William I Walker, Arthur Gretton, Maneesh Sahani

NeurIPSW 2023 Stochastic Linear Dynamics in Parameters to Deal with Neural Networks Plasticity Loss Alexandre Galashov, Michalis Titsias, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani

NeurIPS 2023 Successor-Predecessor Intrinsic Exploration Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J Gershman

AISTATS 2023 Unsupervised Representation Learning with Recognition-Parametrised Probabilistic Models William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani

ICLR 2022 A First-Occupancy Representation for Reinforcement Learning Ted Moskovitz, Spencer R Wilson, Maneesh Sahani

NeurIPS 2022 Structured Recognition for Generative Models with Explaining Away Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani

NeurIPS 2021 Probabilistic Tensor Decomposition of Neural Population Spiking Activity Hugo Soulat, Sepiedeh Keshavarzi, Troy Margrie, Maneesh Sahani

ICML 2020 Amortised Learning by Wake-Sleep Li Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani

NeurIPS 2020 Non-Reversible Gaussian Processes for Identifying Latent Dynamical Structure in Neural Data Virginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin

NeurIPS 2020 Organizing Recurrent Network Dynamics by Task-Computation to Enable Continual Learning Lea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo

NeurIPS 2019 A Neurally Plausible Model Learns Successor Representations in Partially Observable Environments Eszter Vértes, Maneesh Sahani

NeurIPS 2019 A Neurally Plausible Model for Online Recognition and Postdiction in a Dynamical Environment Li Kevin Wenliang, Maneesh Sahani

NeurIPS 2019 Kernel Instrumental Variable Regression Rahul Singh, Maneesh Sahani, Arthur Gretton

ICML 2019 Learning Interpretable Continuous-Time Models of Latent Stochastic Dynamical Systems Lea Duncker, Gergo Bohner, Julien Boussard, Maneesh Sahani

NeurIPS 2018 Flexible and Accurate Inference and Learning for Deep Generative Models Eszter Vértes, Maneesh Sahani

NeurIPS 2018 Temporal Alignment and Latent Gaussian Process Factor Inference in Population Spike Trains Lea Duncker, Maneesh Sahani

NeurIPS 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltan Szabo, Lars Buesing, Maneesh Sahani

JMLR 2014 Efficient Occlusive Components Analysis Marc Henniges, Richard E. Turner, Maneesh Sahani, Julian Eggert, Jörg Lücke

NeurIPS 2013 Extracting Regions of Interest from Biological Images with Convolutional Sparse Block Coding Marius Pachitariu, Adam M Packer, Noah Pettit, Henry Dalgleish, Michael Hausser, Maneesh Sahani

NeurIPS 2013 Recurrent Linear Models of Simultaneously-Recorded Neural Populations Marius Pachitariu, Biljana Petreska, Maneesh Sahani

NeurIPS 2012 Learning Visual Motion in Recurrent Neural Networks Marius Pachitariu, Maneesh Sahani

NeurIPS 2012 Spectral Learning of Linear Dynamics from Generalised-Linear Observations with Application to Neural Population Data Lars Buesing, Jakob H. Macke, Maneesh Sahani

ICML 2012 Variational Inference in Non-Negative Factorial Hidden Markov Models for Efficient Audio Source Separation Gautham J. Mysore, Maneesh Sahani

NeurIPS 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

NeurIPS 2011 Empirical Models of Spiking in Neural Populations Jakob H. Macke, Lars Buesing, John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

NeurIPS 2011 Probabilistic Amplitude and Frequency Demodulation Richard Turner, Maneesh Sahani

NeurIPS 2009 Occlusive Components Analysis Jörg Lücke, Richard Turner, Maneesh Sahani, Marc Henniges

ICML 2008 Fast Gaussian Process Methods for Point Process Intensity Estimation John P. Cunningham, Krishna V. Shenoy, Maneesh Sahani

NeurIPS 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

JMLR 2008 Maximal Causes for Non-Linear Component Extraction Jörg Lücke, Maneesh Sahani

NeurIPS 2007 Inferring Elapsed Time from Stochastic Neural Processes Misha Ahrens, Maneesh Sahani

NeurIPS 2007 Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes John P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani

NeurIPS 2007 Modeling Natural Sounds with Modulation Cascade Processes Richard Turner, Maneesh Sahani

NeurIPS 2007 On Sparsity and Overcompleteness in Image Models Pietro Berkes, Richard Turner, Maneesh Sahani

NeurIPS 2005 Extracting Dynamical Structure Embedded in Neural Activity Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani

NeurIPS 2003 A Biologically Plausible Algorithm for Reinforcement-Shaped Representational Learning Maneesh Sahani

NeCo 2003 Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity Maneesh Sahani, Peter Dayan

NeurIPS 2003 Reconstructing MEG Sources with Unknown Correlations Maneesh Sahani, Srikantan S. Nagarajan

NeurIPS 2002 Adaptation and Unsupervised Learning Peter Dayan, Maneesh Sahani, Gregoire Deback

NeurIPS 2002 Evidence Optimization Techniques for Estimating Stimulus-Response Functions Maneesh Sahani, Jennifer F. Linden

NeurIPS 2002 How Linear Are Auditory Cortical Responses? Maneesh Sahani, Jennifer F. Linden

NeurIPS 1997 On the Separation of Signals from Neighboring Cells in Tetrode Recordings Maneesh Sahani, John S. Pezaris, Richard A. Andersen