Liam Paninski

Q: What Schools Are Affiliated With Liam Paninski

Liam Paninski is affiliated with the following schools: Brown University, University College London, Stanford University, Columbia University, New York University

Liam Paninski's AcademicInfluence.com Rankings

Liam Paninski

Biology

#7700

World Rank

#10659

Historical Rank

Neuroscience

#1021

World Rank

#1063

Historical Rank

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Biology

Liam Paninski's Degrees

PhD Neuroscience New York University
Bachelors Physics Stanford University

Why Is Liam Paninski Influential?

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According to Wikipedia, Liam Paninski is an American computational neuroscientist who specializes in neural data science. He is a professor in the Departments of Statistics and Neuroscience at Columbia University, where he co-directs the Grossman Center for the Statistics of Mind. Paninski's research focuses on using statistics to decipher electrical signals from the brain.

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Liam Paninski's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Estimation of Entropy and Mutual Information (2003) (1338)
Spatio-temporal correlations and visual signalling in a complete neuronal population (2008) (1289)
Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition (2014) (878)
Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data (2016) (791)
Brain-machine interface: Instant neural control of a movement signal (2002) (788)
Maximum likelihood estimation of cascade point-process neural encoding models (2004) (503)
Fast nonnegative deconvolution for spike train inference from population calcium imaging. (2009) (433)
Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data (2016) (393)
Spatiotemporal tuning of motor cortical neurons for hand position and velocity. (2004) (388)
Prediction and Decoding of Retinal Ganglion Cell Responses with a Probabilistic Spiking Model (2005) (365)
Anxiety Cells in a Hippocampal-Hypothalamic Circuit (2018) (343)
Functional connectivity in the retina at the resolution of photoreceptors (2010) (304)
Characterization of Neural Responses with Stochastic Stimuli (2004) (303)
Bright and photostable chemigenetic indicators for extended in vivo voltage imaging (2018) (282)
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model (2004) (282)
Statistical models for neural encoding, decoding, and optimal stimulus design. (2007) (265)
Information about movement direction obtained from synchronous activity of motor cortical neurons. (1998) (258)
Fast online deconvolution of calcium imaging data (2017) (248)
A Coincidence-Based Test for Uniformity Given Very Sparsely Sampled Discrete Data (2008) (247)
Spike inference from calcium imaging using sequential Monte Carlo methods. (2009) (238)
Voltage imaging and optogenetics reveal behavior dependent changes in hippocampal dynamics (2019) (220)
A new look at state-space models for neural data (2010) (205)
Simultaneous Multi-plane Imaging of Neural Circuits (2016) (193)
Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians (2012) (192)
The Spatiotemporal Organization of the Striatum Encodes Action Space (2017) (167)
Convergence properties of three spike-triggered analysis techniques (2003) (158)
Efficient estimation of detailed single-neuron models. (2006) (153)
Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems (2017) (153)
Cerebellar granule cells acquire a widespread predictive feedback signal during motor learning (2017) (149)
BLACK BOX VARIATIONAL INFERENCE FOR STATE SPACE MODELS (2015) (142)
Superlinear Population Encoding of Dynamic Hand Trajectory in Primary Motor Cortex (2004) (138)
Common-input models for multiple neural spike-train data (2007) (134)
Sequential Optimal Design of Neurophysiology Experiments (2009) (133)
Estimating entropy on m bins given fewer than m samples (2004) (133)
Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains (2011) (132)
Linear dynamical neural population models through nonlinear embeddings (2016) (132)
The central amygdala controls learning in the lateral amygdala (2017) (129)
A Generalized Linear Model for Estimating Spectrotemporal Receptive Fields from Responses to Natural Sounds (2011) (122)
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data (2018) (121)
Modeling the impact of common noise inputs on the network activity of retinal ganglion cells (2012) (116)
Asymptotic Theory of Information-Theoretic Experimental Design (2005) (116)
A Bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data (2011) (111)
The Spatiotemporal Organization of the Striatum Encodes Action Space (2017) (109)
Robustness of neuroprosthetic decoding algorithms (2003) (109)
Statistical encoding model for a primary motor cortical brain-machine interface (2005) (104)
Population-Level Representation of a Temporal Sequence Underlying Song Production in the Zebra Finch (2016) (103)
Efficient Coding of Spatial Information in the Primate Retina (2012) (103)
Smoothing of, and Parameter Estimation from, Noisy Biophysical Recordings (2009) (94)
Inferring input nonlinearities in neural encoding models (2008) (86)
Population decoding of motor cortical activity using a generalized linear model with hidden states (2010) (85)
Kalman filter mixture model for spike sorting of non-stationary data (2011) (84)
Spatiotemporal receptive fields of barrel cortex revealed by reverse correlation of synaptic input (2014) (84)
Fast Active Set Methods for Online Deconvolution of Calcium Imaging Data (2016) (81)
NeuroPAL: A Multicolor Atlas for Whole-Brain Neuronal Identification in C. elegans (2020) (79)
Rapid mesoscale volumetric imaging of neural activity with synaptic resolution (2020) (79)
Convergence Properties of Some Spike-Triggered Analysis Techniques (2002) (76)
Complementary networks of cortical somatostatin interneurons enforce layer specific control (2018) (75)
Temporal Precision in the Visual Pathway through the Interplay of Excitation and Stimulus-Driven Suppression (2011) (75)
Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience (2017) (74)
Neural Decoding of Hand Motion Using a Linear State-Space Model With Hidden States (2009) (74)
Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains (2011) (72)
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions (2013) (72)
25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (71)
Mapping nonlinear receptive field structure in primate retina at single cone resolution (2015) (69)
Bayesian spike inference from calcium imaging data (2013) (66)
Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C. elegans (2019) (62)
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model (2003) (61)
Linear encoding of muscle activity in primary motor cortex and cerebellum. (2006) (59)
Robust learning of low-dimensional dynamics from large neural ensembles (2013) (59)
The most likely voltage path and large deviations approximations for integrate-and-fire neurons (2006) (57)
Primacy of Flexor Locomotor Pattern Revealed by Ancestral Reversion of Motor Neuron Identity (2015) (56)
Multilayer Recurrent Network Models of Primate Retinal Ganglion Cell Responses (2016) (55)
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos (2019) (53)
Bayesian Sparse Regression Analysis Documents the Diversity of Spinal Inhibitory Interneurons (2016) (53)
OnACID: Online Analysis of Calcium Imaging Data in Real Time (2017) (51)
Designing optimal stimuli to control neuronal spike timing. (2011) (50)
Hidden Markov Models for the Stimulus-Response Relationships of Multistate Neural Systems (2011) (50)
Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness (2009) (49)
Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions (2013) (49)
An International Laboratory for Systems and Computational Neuroscience (2017) (49)
Inferring synaptic inputs given a noisy voltage trace via sequential Monte Carlo methods (2012) (48)
YASS: Yet Another Spike Sorter (2017) (48)
Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data (2015) (47)
Reinforcement Learning Recruits Somata and Apical Dendrites across Layers of Primary Sensory Cortex (2019) (47)
A low-noise, single-photon avalanche diode in standard 0.13 μm complementary metal-oxide-semiconductor process (2010) (46)
Comparing integrate-and-fire models estimated using intracellular and extracellular data (2005) (46)
Neural Networks for Efficient Bayesian Decoding of Natural Images from Retinal Neurons (2017) (45)
Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays (2016) (44)
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference (2017) (44)
Sequential movement representations based on correlated neuronal activity (2003) (43)
Recurrent switching linear dynamical systems (2016) (43)
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space models (2010) (42)
A structured matrix factorization framework for large scale calcium imaging data analysis (2014) (42)
Fast Active Set Methods for Online Spike Inference from Calcium Imaging (2016) (41)
Real-time adaptive information-theoretic optimization of neurophysiology experiments (2006) (41)
The Spike-Triggered Average of the Integrate-and-Fire Cell Driven by Gaussian White Noise (2006) (40)
Multi-scale approaches for high-speed imaging and analysis of large neural populations (2016) (39)
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking (2020) (38)
NeuroPAL: A Neuronal Polychromatic Atlas of Landmarks for Whole-Brain Imaging in C. elegans (2019) (37)
Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data (2019) (36)
A generalized linear model of the impact of direct and indirect inputs to the lateral geniculate nucleus. (2010) (36)
State-Space Decoding of Goal-Directed Movements (2008) (36)
Multiscale and multimodal reconstruction of cortical structure and function (2020) (36)
Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods (2010) (35)
Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity (2022) (35)
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits (2013) (33)
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data (2018) (32)
Variational Minimax Estimation of Discrete Distributions under KL Loss (2004) (31)
Stochastic Bouncy Particle Sampler (2016) (31)
Noise-driven adaptation: in vitro and mathematical analysis (2003) (31)
Fast Kalman Filtering and Forward–Backward Smoothing via a Low-Rank Perturbative Approach (2014) (31)
Undersmoothed Kernel Entropy Estimators (2008) (31)
Clustered factor analysis of multineuronal spike data (2014) (29)
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations (2020) (29)
Fast inference in generalized linear models via expected log-likelihoods (2013) (28)
Fast Kalman filtering on quasilinear dendritic trees (2010) (27)
Imaging action potentials with calcium indicators. (2009) (26)
Incorporating Naturalistic Correlation Structure Improves Spectrogram Reconstruction from Neuronal Activity in the Songbird Auditory Midbrain (2011) (25)
Chronic, cortex-wide imaging of specific cell populations during behavior (2020) (25)
EMG Prediction From Motor Cortical Recordings via a Nonnegative Point-Process Filter (2012) (24)
Encoder-Decoder Optimization for Brain-Computer Interfaces (2015) (24)
A Bayesian compressed-sensing approach for reconstructing neural connectivity from subsampled anatomical data (2012) (24)
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning (2004) (24)
A multi-agent control framework for co-adaptation in brain-computer interfaces (2013) (23)
YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina (2020) (23)
Statistical models of spike trains (2008) (23)
A shotgun sampling solution for the common input problem in neural connectivity inference (2013) (23)
Model-based decoding, information estimation, and change- point detection in multi-neuron spike trains (2006) (22)
Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model (2008) (22)
Information Rates and Optimal Decoding in Large Neural Populations (2011) (22)
Automating the design of informative sequences of sensory stimuli (2011) (21)
Automated scalable segmentation of neurons from multispectral images (2016) (19)
Neuronal Dynamics: Preface (2014) (17)
A zero-inflated gamma model for post-deconvolved calcium imaging traces (2019) (17)
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders (2021) (16)
Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime (2012) (16)
Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data (2018) (16)
Fast state-space methods for inferring dendritic synaptic connectivity (2013) (16)
Efficient methods for sampling spike trains in networks of coupled neurons (2011) (16)
High fidelity estimates of spikes and subthreshold waveforms from 1-photon voltage imaging in vivo (2020) (15)
Neuroscience Cloud Analysis As a Service (2020) (15)
Flygenvectors: The spatial and temporal structure of neural activity across the fly brain (2021) (15)
A Novel Variational Family for Hidden Nonlinear Markov Models (2018) (15)
Neural Clustering Processes (2019) (15)
Community-based benchmarking improves spike inference from two-photon calcium imaging data (2017) (13)
Neuroprosthetic Decoder Training as Imitation Learning (2015) (13)
BARcode DEmixing through Non-negative Spatial Regression (BarDensr) (2020) (13)
Voltage imaging and optogenetics reveal behaviour-dependent changes in hippocampal dynamics (2019) (13)
General linear-time inference for Gaussian Processes on one dimension (2020) (12)
Partition Functions from Rao-Blackwellized Tempered Sampling (2016) (12)
Neural decoding of goal-directed movements using a linear state-space model with hidden states (2007) (12)
Efficient active learning with generalized linear models (2007) (11)
Nonlinear decoding of natural images from large-scale primate retinal ganglion recordings (2020) (11)
EASE: EM-Assisted Source Extraction from calcium imaging data (2020) (10)
Fast Constrained Non-negative Matrix Factorization for Whole-Brain Calcium Imaging Data (2016) (10)
Bayesian Image Recovery for Dendritic Structures Under Low Signal-to-Noise Conditions (2009) (9)
Nonparametric inference of prior probabilities from Bayes-optimal behavior (2005) (9)
Fast Spatiotemporal Smoothing of Calcium Measurements in Dendritic Trees (2012) (9)
Scalable approximate Bayesian inference for particle tracking data (2018) (8)
Bayesian methods for event analysis of intracellular currents (2016) (8)
Large-scale biophysical parameter estimation in single neurons via constrained linear regression (2005) (8)
Design of Experiments via Information Theory (2003) (7)
Statistical Atlas of C. elegans Neurons (2020) (7)
Scalable variational inference for super resolution microscopy (2016) (7)
On Quadrature Methods for Refractory Point Process Likelihoods (2014) (7)
Monte Carlo methods for localization of cones given multielectrode retinal ganglion cell recordings (2013) (6)
Improved numberical methods for computing likelihoods in the stochastic integrate-and-fire model (2005) (6)
Demixing Calcium Imaging Data in C. elegans via Deformable Non-negative Matrix Factorization (2020) (6)
Sinkhorn Permutation Variational Marginal Inference (2019) (5)
Fast interior-point inference in high-dimensional sparse, penalized state-space models (2012) (5)
Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis (2022) (5)
Three-dimensional spike localization and improved motion correction for Neuropixels recordings (2021) (5)
Maximally Reliable Markov Chains Under Energy Constraints (2009) (5)
An expectation-maximization Fokker-Planck algorithm for the noisy integrate-and-fir e model (2007) (5)
Probabilistic Joint Segmentation and Labeling of C. elegans Neurons (2020) (5)
Low rank continuous-space graphical models (2012) (5)
Efficient characterization of electrically evoked responses for neural interfaces (2019) (5)
Amortized Bayesian inference for clustering models (2018) (5)
Reproducibility of in-vivo electrophysiological measurements in mice (2022) (5)
Robust and scalable Bayesian analysis of spatial neural tuning function data (2016) (4)
Dendrites and synapses (2014) (4)
High-fidelity estimates of spikes and subthreshold waveforms from 1-photon voltage imaging in vivo. (2021) (4)
Decoding arm and hand movements across layers of the macaque frontal cortices (2012) (4)
State-space methods for inferring synaptic inputs and weights (2007) (4)
Near-optimal experimental design for sampling voltage on dendritic trees (2010) (4)
Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization (2020) (4)
Decentralized Motion Inference and Registration of Neuropixel Data (2021) (4)
Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds (2008) (4)
Nonlinear integrate-and-fire models (2014) (3)
Mapping a Neural Circuit : A Complete Input-Output Diagram in the Primate Retina (2010) (3)
Attentive Clustering Processes (2020) (3)
Visualizing the organization and differentiation of the male-specific nervous system of C. elegans (2021) (3)
Neuronal Dynamics: Variability of spike trains and neural codes (2014) (3)
The relationship between optimal and biologically plausible decoding of stimulus velocity in the retina. (2009) (3)
Computing loss of efficiency in optimal Bayesian decoders given noisy or incomplete spike trains (2013) (3)
Discrete Neural Processes (2018) (3)
Robust particle filters via sequential pairwise reparameterized Gibbs sampling (2012) (3)
Spike Sorting using the Neural Clustering Process (2019) (3)
Model-based optimal interpolation and ltering for noisy, intermittent biophysical recordings (2006) (3)
A Statistical Model of Shared Variability in the Songbird Auditory System (2017) (2)
Random-Access Multiphoton (RAMP) Microscopy Fast Functional Imaging of Single Neurons Using (2006) (2)
Neural Permutation Processes (2019) (2)
Modelbased optimal interpolation and filtering for noisy, intermittend, biophysical signals (2006) (2)
Neuronal Dynamics: Synaptic plasticity and learning (2014) (2)
GENERALIZED INTEGRATE-AND-FIRE NEURONS (2014) (2)
Visualizing the organization and differentiation of the male-specific nervous system of C. elegans. (2021) (2)
Fast Kalman filtering via a low-rank perturbative approach (2011) (2)
Inference From Population Calcium Imaging Fast Nonnegative Deconvolution for Spike Train (2010) (2)
Semi-supervised sequence modeling for improved behavioral segmentation (2021) (2)
Analysis of functional imaging data at single-cellular resolution ∗ (2018) (2)
Statistical Research and Training Under the Brain Initiative (2014) (2)
A Bayesian compressed-sensing approach for reconstructing neural connectivity from subsampled anatomical data (2012) (2)
Direct measurement of “suppression” in the LGN in the context of natural stimuli and its implications for visual coding (2006) (1)
Novel Model-based identification of retinal ganglion cell subunits (2016) (1)
Memory and attractor dynamics (2014) (1)
Statistical analysis of neural data : Generalized linear models for spike trains (2007) (1)
Statistical analysis of neural data : State-space models and applications to optimal voltage smoothing , tracking nonstationarities , and recursive decoding (2007) (1)
Spatio-temporalcorrelationsandvisualsignallingina complete neuronal population (2008) (1)
Adaptation and firing patterns (2014) (1)
Neuronal Dynamics: Estimating parameters of probabilistic neuron models (2014) (1)
E � cient and accurate extraction of 1 in vivo calcium signals from 2 microendoscopic video data (2018) (1)
Neuronal Dynamics: Competing populations and decision making (2014) (1)
SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework (2022) (1)
Amortized Probabilistic Detection of Communities in Graphs (2020) (1)
Versatile Multiple Object Tracking in Sparse 2D/3D Videos Via Diffeomorphic Image Registration (2022) (1)
A general linear-time inference method for Gaussian Processes on one dimension (2021) (1)
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models (2019) (1)
Inferring the Structure of Populations of Neurons using a Sequential Monte Carlo EM Algorithm (2006) (1)
Efficient model-based design of neurophysiological experiments (2006) (1)
Robust Online Multiband Drift Estimation in Electrophysiology Data (2023) (1)
Blind demixing methods for recovering dense neuronal morphology from barcode imaging data (2021) (1)
The Markov link method: a nonparametric approach to combine observations from multiple experiments (2018) (1)
Introduction: neurons and mathematics (2014) (1)
Non-parametric Vignetting Correction for Sparse Spatial Transcriptomics Images (2021) (1)
Optimal decoding of stimulus velocity using a probabilistic model of ganglion cell populations in primate retina (2009) (1)
Statistical analysis of neural data: Classification-based approaches: spike-triggered averaging, spike-triggered covariance, and the linear-nonlinear cascade model (2007) (1)
Rapid mesoscale volumetric imaging of neural activity with synaptic resolution (2020) (0)
An Efficient Algorithm for Sequential Optimal Design of Neuro- physiology Experiments (2007) (0)
DYNAMICS OF COGNITION (2014) (0)
Statistical analysis of neural data : Discrete-space hidden Markov models (2009) (0)
Neuronal Dynamics: Continuity equation and the Fokker–Planck approach (2014) (0)
Fast inference in generalized linear models via expected log-likelihoods (2013) (0)
Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime (2011) (0)
A Bayesian method to predict the optimal diffusion coefficient in random fixational eye movements (2009) (0)
Towards Confirming Cosyne 2010 (2015) (0)
Neuronal Dynamics: Outlook: dynamics in plastic networks (2014) (0)
Towards Confirming Neural Circuit Inference from Population Calcium Imaging. NIPS Workshop on Connectivity Inference in Neuroimaging (2015) (0)
A new method to analyze the variations of neural tuning and its application to primate V1 (2019) (0)
Hidden Markov models for the stimulus-response relationships of multi-state neurons (2009) (0)
Multilinear neural encoding models capture nonlinearities and contextual influences in cortical responses (2007) (0)
Statistical analysis of neural data : Maximum a posteriori techniques for decoding spike trains (2007) (0)
Neuronal Dynamics: Noisy output: escape rate and soft threshold (2014) (0)
Correction: Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data (2015) (0)
M L ] 1 4 M ar 2 01 6 Neuroprosthetic decoder training as imitation learning (2018) (0)
Statistical analysis of neural data : Continuous-space models ( First 2 / 3 ) (2009) (0)
Inferring synaptic inputs given a noisy voltage trace via sequential Monte Carlo methods (2011) (0)
Neuronal Dynamics: NETWORKS OF NEURONS AND POPULATION ACTIVITY (2014) (0)
Fast state-space methods for inferring dendritic synaptic connectivity (2013) (0)
Towards Inferring Neural Circuits from Calcium Population Imaging (2015) (0)
Multimodal Microscopy Image Alignment Using Spatial and Shape Information and a Branch-and-Bound Algorithm (2023) (0)
Statistical analysis of neural data : Monte Carlo techniques for decoding spike trains (2007) (0)
Neuronal Dynamics: Fast transients and rate models (2014) (0)
Noise-Driven Adaptation: and Mathematical Analysis (2002) (0)
Statistical analysis of neural data : Regression approaches for modeling neural responses and stimulus decoding (2013) (0)
Deep Networks for Decoding Natural Images from Retinal Signals (2017) (0)
Statistical analysis of neural data: Hidden Markov models and applications to multi-state neural models ∗ (2007) (0)
Integrate-and-fire-based neural encoding models (2007) (0)
REVERSE CORRELATION ANALYSIS OF THALAMIC RESPONSES TO DYNAMIC WHISKER STIMULATION (2006) (0)
Model-based smoothing of noisy, intermittent, biophysical signals (2007) (0)
Efficient adaptive experimental design (2009) (0)
From Calcium Sensitive Fluorescence Movies to Spike Trains (2015) (0)
Implementing e cient "shotgun" inference of neural connectivity from highly sub-sampled activity data (2015) (0)
Model-based optimal inference of spike times and calcium dy- namics given noisy and intermittent calcium-fluorescence imag- ing (2007) (0)
Dimensionality reduction and phase plane analysis (2014) (0)
Rapid learning of neural circuitry from holographic ensemble stimulation enabled by model-based compressed sensing (2022) (0)
Statistical analysis of neural data: Addenda to Brown's point process notes (2007) (0)
Ion channels and the Hodgkin–Huxley model (2014) (0)
Statistical methods for understanding neural codes (2006) (0)
Two-photon multiplane imaging of neural circuits (Conference Presentation) (2016) (0)
Maximum Likelihood Inference of Neuronal Dynamics under Noisy and Intermittent Observations using Sequential Monte Carlo EM Algorithms (2015) (0)
Bayesian image recovery for low-SNR dendritic structures (2006) (0)
Modeling the impact of common noise inputs on the network activity of retinal ganglion cells (2011) (0)
Stochastic optimal control and the human oculomotor system (2001) (0)
Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools (2023) (0)
Cortical field models for perception (2014) (0)
Encoding and decoding with stochastic neuron models (2014) (0)
Bayesian Sparse Unsupervised Learning for Probit Models of Binary Data (2014) (0)
Noisy input models: barrage of spike arrivals (2014) (0)
Statistical analysis of neural data : The integrate-and-fire neuron and other continuous-time state-space models (2007) (0)
Cat Lateral Geniculate Nucleus Variability and Information in a Neural Code of the (2015) (0)
Quasi-renewal theory and the integral-equation approach (2014) (0)
Motor Cortex and Cerebellum Linear Encoding of Muscle Activity in Primary (2006) (0)
Statistical analysis of neural data : The expectation-maximization ( EM ) algorithm (2007) (0)
Statistical methods for understanding complex biophysical neural data (2007) (0)
25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (0)
Movements Under Resistive and Assistive Force Fields Encoding of Movement Dynamics by Purkinje Cell Simple Spike Activity During Fast Arm (2008) (0)
NeuroResource Simultaneous Denoising , D econvolution , and Demixing of Calcium Imaging Data Highlights (2016) (0)
Disentangled sticky hierarchical Dirichlet process hidden Markov model (2020) (0)
The central amygdala controls learning in the lateral amygdala (2017) (0)
Inferring Spike Trains, Learning Tuning Curves, and Estimating Connectivity from Calcium Imaging (2015) (0)
The Spatiotemporal Organ ization of the Striatum Encodes Action Space Highlights (2018) (0)
Inferring Spike Trains, Neural Filters, and Network Circuits from in vivo Calcium Imaging (2015) (0)
Toward characterizion of the complete visual signal in a patch of retina (2010) (0)

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