C. Rozell

发表

Learning Sparse Codes for Hyperspectral Imagery

Bruno A. Olshausen, Christopher J. Rozell, Adam S. Charles, 2011, IEEE Journal of Selected Topics in Signal Processing.

Sparse coding for spectral signatures in hyperspectral images

Adam S. Charles, B. Olshausen, C. Rozell, 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

Sparse Coding via Thresholding and Local Competition in Neural Circuits

Richard G. Baraniuk, Bruno A. Olshausen, Don H. Johnson, 2008, Neural Computation.

Visual Nonclassical Receptive Field Effects Emerge from Sparse Coding in a Dynamical System

Christopher J. Rozell, Mengchen Zhu, C. Rozell, 2013, PLoS Comput. Biol..

The Restricted Isometry Property for block diagonal matrices

Michael B. Wakin, Christopher J. Rozell, Armin Eftekhari, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

Concentration of Measure for Block Diagonal Matrices with Applications to Compressive Sensing

M. Wakin, C. Rozell, H. Yap, 2010 .

Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices

C. Rozell, I. Nemenman, Arish Alreja, 2020, bioRxiv.

All-optical nanoscale pH meter.

B. R. Johnson, Don H. Johnson, C. Rozell, 2006, Nano letters.

Discrete and Continuous-time Soft-Thresholding with Dynamic Inputs

J. Romberg, C. Rozell, A. Balavoine, 2014, 1405.1361.

Stabilizing embedology: Geometry-preserving delay-coordinate maps.

Christopher J Rozell, Armin Eftekhari, Han Lun Yap, 2016, Physical review. E.

Sparsity Based Spectral Super-Resolution and Applications to Ocean Water Color

Christopher J. Rozell, Nicholas B. Tufillaro, Adam S. Charles, 2014, IGARSS 2014.

Robust Incorporation of Signal Predictions into the Sparse Bayesian Learning Framework

M. Davenport, C. Rozell, Matthew R. O’Shaughnessy, 2019 .

Oracle Guided Image Synthesis with Relative Queries

C. Rozell, Matthew R. O’Shaughnessy, Alec Helbling, 2022, 2204.14189.

Analog sparse approximation for compressed sensing recovery

Christopher J. Rozell, Pierre Garrigues, C. Rozell, 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

Sparse Coding via Thresholding and Local Competition

Richard G. Baraniuk, Bruno A. Olshausen, Don H. Johnson, 2006 .

Stable Takens' Embeddings for Linear

C. Rozell, H. Yap, H. L. Yap, 2011 .

Variational Sparse Coding with Learned Thresholding

C. Rozell, Kion Fallah, 2022, 2205.03665.

Neurally plausible sparse coding via local competition and thresholding

Richard Baraniuk, Don H. Johnson, C. Rozell, 2022 .

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Adam S. Charles, C. Rozell, Eva Yezerets, 2022, ArXiv.

A Low-Complexity Brain–Computer Interface for High-Complexity Robot Swarm Control

Gregory H. Canal, M. Egerstedt, C. Rozell, 2022, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

SIMULINK MODELING AND IMPLEMENTATION OF CMOS DENDRITES USING FPAA

David V. Anderson, C. Rozell, Stephen Nease, 2011 .

FOR ASSESSING CHANGES IN CROSS-FREQUENCY COUPLING DUE TO DEEP BRAIN STIMULATION THERAPIES FOR TREATMENT RESISTANT DEPRESSION

C. Rozell, Rehman Ali, Tyrone Pannkuk, 2016 .

Multi-Modal Assessment and Treatment of Chronic Headache: The First in a Series of Case Studies

C. Rozell, C. C. Donaldson, P. Moran, 2012 .

Variational Sparse Coding with Learned Thresholding

C. Rozell, Kion Fallah, 2022, ICML.

Neural architectures for sparse approximation

Bruno A. Olshausen, Richard G. Baraniuk, Don H. Johnson, 2008 .

Power Scheduling for Wireless Sensor and Actuator Networks

Don H. Johnson, Christopher J. Rozell, Don H. Johnson, 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

Information Theory and Neuroscience: A Tutorial

Don H. Johnson, Christopher J. Rozell, Ilan N. Goodman, 2006 .

Passively Captured Interpersonal Social Interactions and Motion From Smartphones for Predicting Decompensation in Heart Failure: Observational Cohort Study

E. A. Perez Alday, Ayse S. Cakmak, C. Rozell, 2022, JMIR formative research.

Variational Autoencoder with Learned Latent Structure pdf

Christopher J. Rozell, Gregory H. Canal, Marissa C. Connor, 2020, AISTATS.

Learning sparse codes from compressed representations with biologically plausible local wiring constraints

Christopher J. Rozell, Ninghao Liu, Kion Fallah, 2020, bioRxiv.

Modeling Inhibitory Interneurons in Efficient Sensory Coding Models

Christopher J. Rozell, Mengchen Zhu, C. Rozell, 2015, PLoS Comput. Biol..

Optimal Sparse Approximation with Integrate and Fire Neurons

Christopher J. Rozell, Jennifer Hasler, Mengchen Zhu, 2014, Int. J. Neural Syst..

A Common Network Architecture Efficiently Implements a Variety of Sparsity-Based Inference Problems

Christopher J. Rozell, Adam S. Charles, Pierre Garrigues, 2012, Neural Computation.

Biologically realistic excitatory and inhibitory cell properties emerge from a sparse coding network

C. Rozell, Mengchen Zhu, 2012, BMC Neuroscience.

Convergence and Rate Analysis of Neural Networks for Sparse Approximation

Justin K. Romberg, Christopher J. Rozell, Aurele Balavoine, 2011, IEEE Transactions on Neural Networks and Learning Systems.

Sparse coding models demonstrate some non-classical receptive field effects

Mengchen Zhu, Christopher J Rozell, C. Rozell, 2010, BMC Neuroscience.

Distributed redundant representations in man-made and biological sensing systems

Christopher J. Rozell, C. Rozell, 2007 .

Supporting Information: Text S1

C. Rozell, Mengchen Zhu, W. Coulter, 2013 .

A first analysis of the stability of Takens' embedding

Michael B. Wakin, Christopher J. Rozell, Armin Eftekhari, 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Stable Takens' Embeddings for Linear Dynamical Systems

Christopher J. Rozell, Han Lun Yap, C. Rozell, 2010, IEEE Transactions on Signal Processing.

Distributed processing in frames for sparse approximation

Christopher J. Rozell, C. Rozell, 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

Power Scheduling for Wireless Sensor and Actuator Networks

D.H. Johnson, C.J. Rozell, Don H. Johnson, 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

Evaluating Local Contributions to Global Performance in Wireless Sensor and Actuator Networks

Don H. Johnson, Christopher J. Rozell, Don H. Johnson, 2006, DCOSS.

Modeling wireless sensor and actuator networks using frame theory

Don H. Johnson, Christopher J. Rozell, Don H. Johnson, 2005 .

Short-term Sequence Memory: Compressive effects of Recurrent Network Dynamics

Christopher J. Rozell, Adam S. Charles, Dong Yin, 2018 .

Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks

Christopher J. Rozell, Adam S. Charles, Dong Yin, 2016, J. Mach. Learn. Res..

Cell Membrane Tracking in Living Brain Tissue Using Differential Interference Contrast Microscopy

Christopher J. Rozell, Ilya Kolb, John Lee, 2018, IEEE Transactions on Image Processing.

Fast ADMM solver for reweighted total variation image deconvolution and inpainting

Christopher J. Rozell, John Lee, C. Rozell, 2017, 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Learning Identity-Preserving Transformations on Data Manifolds

C. Rozell, Kion Fallah, Marissa Connor, 2021, Trans. Mach. Learn. Res..

Representing Closed Transformation Paths in Encoded Network Latent Space

Marissa Connor, Christopher Rozell, C. Rozell, 2019, AAAI.

Matched filter performance for unequal target and background covariance matrices

Christopher J. Rozell, Dimitris G. Manolakis, C. Rozell, 2004, SPIE Defense + Commercial Sensing.

Information-Theoretic Analysis of Neural Responses in the Frequency Domain

Christopher Rozell, C. Rozell, 2003 .

Type-based Detection of Pure Tones in an Auditory Nerve Model

Christopher John Rozell, C. Rozell, 2003 .

Parallel Unbalanced Optimal Transport Regularization for Large Scale Imaging Problems

Nicholas P. Bertrand, C. Rozell, John Lee, 2019, 1909.00149.

State-space optimal feedback control of optogenetically driven neural activity

G B Stanley, M F Bolus, A A Willats, 2020, bioRxiv.

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

G B Stanley, M F Bolus, A A Willats, 2018, Journal of neural engineering.

Sparse Coding Using the Locally Competitive Algorithm on the TrueNorth Neurosynaptic System

David V. Anderson, Andreas G. Andreou, Christopher J. Rozell, 2019, Front. Neurosci..

Configurable hardware integrate and fire neurons for sparse approximation

Christopher J. Rozell, Paul E. Hasler, Samuel A. Shapero, 2013, Neural Networks.

Convergence of a neural network for sparse approximation using the nonsmooth Łojasiewicz inequality

Justin K. Romberg, Christopher J. Rozell, Aurele Balavoine, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Low Power Sparse Approximation on Reconfigurable Analog Hardware

Christopher J. Rozell, Adam S. Charles, Paul E. Hasler, 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

A sparse coding model of V1 produces surround suppression effects in response to natural scenes

Allison Del Giorno, C. Rozell, Mengchen Zhu, 2013, BMC Neuroscience.

The Restricted Isometry Property for Random Block Diagonal Matrices pdf

Michael B. Wakin, Christopher J. Rozell, Armin Eftekhari, 2012, ArXiv.

Generative causal explanations of black-box classifiers pdf

Marissa Connor, Matthew O'Shaughnessy, Gregory Canal, 2020, NeurIPS.

Discrete and Continuous-Time Soft-Thresholding for Dynamic Signal Recovery

Justin K. Romberg, Christopher J. Rozell, Aurele Balavoine, 2014, IEEE Transactions on Signal Processing.

PrefGen: Preference Guided Image Generation with Relative Attributes

C. Rozell, Matthew R. O’Shaughnessy, Alec Helbling, 2023, arXiv.org.

Active Embedding Search via Noisy Paired Comparisons

Christopher J. Rozell, Mark A. Davenport, Andrew K. Massimino, 2019, 2020 Information Theory and Applications Workshop (ITA).

Convergence of basis pursuit de-noising with dynamic filtering

Christopher J. Rozell, Adam S. Charles, C. Rozell, 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Dynamic filtering of sparse signals using reweighted ℓ1

Christopher J. Rozell, Adam S. Charles, C. Rozell, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Sparsity penalties in dynamical system estimation

Justin K. Romberg, Christopher J. Rozell, M. Salman Asif, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer

Christopher J. Rozell, Nicholas P. Bertrand, Adam S. Charles, 2018, IEEE Signal Processing Letters.

Sparse Bayesian Learning With Dynamic Filtering for Inference of Time-Varying Sparse Signals

M. Davenport, C. Rozell, Matthew R. O’Shaughnessy, 2019, IEEE Transactions on Signal Processing.

Sub-second dynamics of theta-gamma coupling in hippocampal CA1

Lu Zhang, Annabelle C Singer, Christopher Rozell, 2019, eLife.

Can random linear networks store multiple long input streams?

Christopher J. Rozell, Adam S. Charles, Dong Yin, 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

Short-Term Memory Capacity in Networks via the Restricted Isometry Property

Christopher J. Rozell, Adam S. Charles, Han Lun Yap, 2013, Neural Computation.

The Restricted Isometry Property for Echo State Networks with applications to sequence memory capacity

Christopher J. Rozell, Adam S. Charles, Han Lun Yap, 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

Compression of multiple input streams into recursive neural networks

Christopher J. Rozell, Adam S. Charles, Dong Yin, 2017 .

Short-Term Memory Capacity in Recurrent Networks via Compressed Sensing

Christopher J. Rozell, Adam S. Charles, Han Lun Yap, 2012 .

Hierarchical Optimal Transport for Multimodal Distribution Alignment pdf

Eva L. Dyer, Christopher J. Rozell, John Lee, 2019, NeurIPS.

Active Ordinal Querying for Tuplewise Similarity Learning

Gregory H. Canal, C. Rozell, Stefano Fenu, 2019, AAAI.

Harnessing the Manifold Structure of Cardiomechanical Signals for Physiological Monitoring During Hemorrhage

Omer Inan, Christopher J Rozell, Jacob Kimball, 2020, IEEE Transactions on Biomedical Engineering.

Modeling sensor networks with fusion frames

Peter G. Casazza, Gitta Kutyniok, Christopher J. Rozell, 2007, SPIE Optical Engineering + Applications.

Analysis of noise reduction in redundant expansions under distributed processing requirements

Don H. Johnson, Christopher J. Rozell, Don H. Johnson, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Manifold Contrastive Learning with Variational Lie Group Operators

C. Rozell, Alec Helbling, Kion Fallah, 2023, ArXiv.

Learning Internal Representations of 3D Transformations from 2D Projected Inputs

Bruno Olshausen, B. Olshausen, C. Rozell, 2023, ArXiv.

Unsupervised learning of manifold models for neural coding of physical transformations in the ventral visual pathway

Christopher J. Rozell, Marissa Connor, C. Rozell, 2016, NIPS 2016.

An unbiased, efficient sleep-wake detection algorithm for a population with sleep disorders: Change Point Decoder.

Gari D Clifford, Giulia Da Poian, Amit J Shah, 2020, Sleep.

PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices

John Lee, Bo Yang, Edward S Boyden, 2019, Journal of neural engineering.

Matched Filtering for Heart Rate Estimation on Compressive Sensing ECG Measurements

Riccardo Bernardini, Giulia Da Poian, Christopher J Rozell, 2018, IEEE Transactions on Biomedical Engineering.

Earth-Mover's distance as a tracking regularizer

Christopher J. Rozell, Nicholas P. Bertrand, John Lee, 2017, 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Dynamic Filtering of Time-Varying Sparse Signals via $\ell _1$ Minimization

Christopher J. Rozell, Adam S. Charles, Aurele Balavoine, 2015, IEEE Transactions on Signal Processing.

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding

Christopher J Rozell, Daniel C Millard, Garrett B Stanley, 2015, The Journal of Neuroscience.

Distance preservation in state-space methods for detecting causal interactions in dynamical systems

C. Rozell, Matthew R. O’Shaughnessy, M. Davenport, 2023, ArXiv.

A 17.8-MS/s Compressed Sensing Radar Accelerator Using a Spiking Neural Network

Michael J. Flynn, Justin Romberg, Christopher J. Rozell, 2020, IEEE Journal of Solid-State Circuits.

Dynamical System Implementations of Sparse Bayesian Learning

Mark A. Davenport, Christopher J. Rozell, Matthew R. O'Shaughnessy, 2019, 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Analog Sparse Approximation with Applications to Compressed Sensing

Christopher J. Rozell, Adam S. Charles, Pierre Garrigues, 2011, 1111.4118.

Unbalanced Optimal Transport Regularization for Imaging Problems

Christopher J. Rozell, Nicholas P. Bertrand, John Lee, 2020, IEEE Transactions on Computational Imaging.

Spectral Superresolution of Hyperspectral Imagery Using Reweighted $\ell_{1}$ Spatial Filtering

Christopher J. Rozell, Adam S. Charles, C. Rozell, 2014, IEEE Geoscience and Remote Sensing Letters.

Stable Manifold Embeddings With Structured Random Matrices

Michael B. Wakin, Christopher J. Rozell, Han Lun Yap, 2012, IEEE Journal of Selected Topics in Signal Processing.

Stable manifold embeddings with operators satisfying the Restricted Isometry Property

Michael B. Wakin, Christopher J. Rozell, Han Lun Yap, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

On the Relation between Block Diagonal Matrices and Compressive Toeplitz Matrices

Christopher J. Rozell, Han Lun Yap, C. Rozell, 2011 .

Feedback Coding for Active Learning pdf

Matthieu Bloch, Gregory Canal, Christopher Rozell, 2021, AISTATS.

Fast Numerical Methods for Convex Problems with Optimal Transport Regularization

C. Rozell, John Lee, 2019 .

Convergence Speed of a Dynamical System for Sparse Recovery

Justin K. Romberg, Christopher J. Rozell, Aurele Balavoine, 2013, IEEE Transactions on Signal Processing.

Transcutaneous Cervical Vagus Nerve Stimulation Reduces Respiratory Variability in the Context of Opioid Withdrawal

Asim H. Gazi, Anna B. Harrison, C. Rozell, 2022, 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

Joint Estimation of Trajectory and Dynamics from Paired Comparisons

Mark A. Davenport, Christopher J. Rozell, Matthew R. O'Shaughnessy, 2019, 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Adam S. Charles, C. Rozell, Eva Yezerets, 2022, ArXiv.

Re-Weighted l_1 Dynamic Filtering for Time-Varying Sparse Signal Estimation

Christopher J. Rozell, Adam S. Charles, C. Rozell, 2012, 1208.0325.

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

C. Rozell, C. Whitmire, M. Bolus, 2018, Journal of neural engineering.

Feature-Based Information Processing with Selective Attention

Don H. Johnson, Christopher J. Rozell, Ilan N. Goodman, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Measuring information transfer in the spike generator of crayfish sustaining fibers

Don H. Johnson, Christopher J. Rozell, Raymon M. Glantz, 2004, Biological Cybernetics.

Information processing during transient responses in the crayfish visual system

Don H. Johnson, Christopher J. Rozell, Raymon M. Glantz, 2003, Neurocomputing.

Analyzing dynamics and stimulus feature dependence in the information processing of crayfish sustaining fibers

Christopher J. Rozell, C. Rozell, 2002 .

Information Theory and Systems Neuroscience

Don H. Johnson, Christopher J. Rozell, Ilan N. Goodman, 2010 .

QUANTIFYING INFORMATION PROCESSING IN A SENSORINEURAL SYSTEM

Don H. Johnson, C. Rozell, 2001 .

Precision cell boundary tracking on DIC microscopy video for patch clamping

Christopher J. Rozell, John Lee, C. Rozell, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Estimation and dynamic updating of time-varying signals with sparse variations

Justin K. Romberg, Christopher J. Rozell, M. Salman Asif, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Theoretical Framework for Electro-Acoustic Music

Gregory H. Wakefield, Mary Simoni, Colin Meek, 1999, ICMC.

Locally Competitive Algorithms for Sparse Approximation

Richard G. Baraniuk, Bruno A. Olshausen, Don H. Johnson, 2007, 2007 IEEE International Conference on Image Processing.

Neurally plausible sparse coding via thresholding and local competition

Richard G. Baraniuk, Bruno A. Olshausen, Don H. Johnson, 2007 .

Sparse coding model captures V1 population response statistics to natural movies

Mengchen Zhu, Christopher J Rozell, Bruno A Olshausen, 2013, BMC Neuroscience.