Adam S. Charles

48 papers A* 5A 1Misc 6Journal 29Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Behavior-dLDS: A decomposed linear dynamical systems model for neural activity partially constrained by behavior.
CoRR
Eva Yezerets, En Yang, Misha B. Ahrens, Adam S. Charles
2026 J jnl
Fast and accessible morphology-free functional fluorescence imaging analysis.
PLoS Comput. Biol.
Alejandro Estrada Berlanga, Gabrielle Y. Kang, Amanda Kwok, Thomas Broggini, Jennifer Lawlor, Kishore V. Kuchibhotla, David Kleinfeld, Gal Mishne, Adam S. Charles
2026 J jnl
Multi-Integration of Labels across Categories for Component Identification (MILCCI).
CoRR
Noga Mudrik, Yuxi Chen, Gal Mishne, Adam S. Charles
2025 A conf
Data mining the functional architecture of the brain's circuitry.
SDM
Adam S. Charles
2024 — conf
Cellular-Resolution Image-Guided Localization in the Primate Brain.
EMBC
Jacob Stefanowicz, John S. Choi, Katie Wingel, Jarl Haggerty, Adam S. Charles, Bijan Pesaran
2024 J jnl
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics.
J. Mach. Learn. Res.
Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles
2024 J jnl
Deep and shallow data science for multi-scale optical neuroscience.
CoRR
Gal Mishne, Adam S. Charles
2024 J jnl
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability.
CoRR
Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher Rozell, Adam S. Charles
2024 J jnl
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training.
CoRR
Jiancheng Xie, Lou C. Kohler Voinov, Noga Mudrik, Gal Mishne, Adam S. Charles
2024 A* conf
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics.
NeurIPS
Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam Alagapan, Adam S. Charles, Christopher Rozell
2024 J jnl
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics.
CoRR
Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam Alagapan, Adam S. Charles, Christopher J. Rozell
2024 A* conf
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States.
ICML
Noga Mudrik, Gal Mishne, Adam S. Charles
2024 J jnl
Sparse-Coding Variational Autoencoders.
Neural Comput.
Victor Geadah, Gabriel Barello, C. Daniel Greenidge, Adam S. Charles, Jonathan W. Pillow
2024 J jnl
Unsupervised discovery of the shared and private geometry in multi-view data.
CoRR
Sai Koukuntla, Joshua B. Julian, Jesse C. Kaminsky, Manuel Schottdorf, David W. Tank, Carlos D. Brody, Adam S. Charles
2024 A* conf
realSEUDO for real-time calcium imaging analysis.
NeurIPS
Iuliia Dmitrieva, Sergey Babkin, Adam S. Charles
2023 — conf
Prospective Learning: Principled Extrapolation to the Future.
CoLLAs
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam S. Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
2023 J jnl
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States.
CoRR
Noga Mudrik, Gal Mishne, Adam S. Charles
2022 J jnl
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics.
CoRR
Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles
2022 J jnl
GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging.
IEEE Trans. Image Process.
Adam S. Charles, Nathan Cermak, Rifqi O. Affan, Benjamin B. Scott, Jackie Schiller, Gal Mishne
2022 J jnl
Multi-Lingual DALL-E Storytime.
CoRR
Noga Mudrik, Adam S. Charles
2022 J jnl
Prospective Learning: Back to the Future.
CoRR
Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
2021 J jnl
An Efficient and Flexible Spike Train Model Via Empirical Bayes.
IEEE Trans. Signal Process.
Qi She, Xiaoli Wu, Beth Jelfs, Adam S. Charles, Rosa H. M. Chan
2020 J jnl
Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer.
IEEE Signal Process. Lett.
Nicholas P. Bertrand, Adam S. Charles, John Lee, Pavel Dunn, Christopher J. Rozell
2020 A* conf
Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield.
NeurIPS
John S. Choi, Krishan Kumar, Mohammad Khazali, Katie Wingel, Mahdi Choudhury, Adam S. Charles, Bijan Pesaran
2019 Misc conf
Learning Spatially-correlated Temporal Dictionaries for Calcium Imaging.
ICASSP
Gal Mishne, Adam S. Charles
2019 A* conf
Visualizing the PHATE of Neural Networks.
NeurIPS
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
2019 J jnl
Visualizing the PHATE of Neural Networks.
CoRR
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
2018 J jnl
Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability.
Neural Comput.
Adam S. Charles, Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow
2018 J jnl
Interpreting Deep Learning: The Machine Learning Rorschach Test?
CoRR
Adam S. Charles
2018 Misc conf
Sparse Dynamic Filtering via Earth Mover's Distance Regularization.
ICASSP
Nicholas P. Bertrand, John Lee, Adam S. Charles, Pavel Dunn, Christopher J. Rozell
2017 J jnl
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks.
J. Mach. Learn. Res.
Adam S. Charles, Dong Yin, Christopher J. Rozell
2017 — conf
Earth-Mover's distance as a tracking regularizer.
CAMSAP
Adam S. Charles, Nicholas P. Bertrand, John Lee, Christopher J. Rozell
2017 Misc conf
Stochastic filtering of two-photon imaging using reweighted ℓ1.
ICASSP
Adam S. Charles, Alexander Song, Sue Ann Koay, David W. Tank, Jonathan W. Pillow
2016 J jnl
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks.
CoRR
Adam S. Charles, Dong Yin, Christopher J. Rozell
2016 J jnl
Dynamic Filtering of Time-Varying Sparse Signals via ℓ
IEEE Trans. Signal Process.
Adam S. Charles, Aurele Balavoine, Christopher J. Rozell
2015 — —
Dynamics and correlations in sparse signal acquisition.
Adam S. Charles
2014 — conf
Can random linear networks store multiple long input streams?
GlobalSIP
Adam S. Charles, Dong Yin, Christopher J. Rozell
2014 — conf
Convergence of basis pursuit de-noising with dynamic filtering.
GlobalSIP
Adam S. Charles, Christopher J. Rozell
2014 J jnl
Short-Term Memory Capacity in Networks via the Restricted Isometry Property.
Neural Comput.
Adam S. Charles, Han Lun Yap, Christopher J. Rozell
2014 J jnl
Spectral Superresolution of Hyperspectral Imagery Using Reweighted ℓ
IEEE Geosci. Remote. Sens. Lett.
Adam S. Charles, Christopher J. Rozell
2013 Misc conf
Dynamic filtering of sparse signals using reweighted ℓ1.
ICASSP
Adam S. Charles, Christopher J. Rozell
2013 J jnl
Short Term Memory Capacity in Networks via the Restricted Isometry Property.
CoRR
Adam S. Charles, Han Lun Yap, Christopher J. Rozell
2012 J jnl
A Common Network Architecture Efficiently Implements a Variety of Sparsity-Based Inference Problems.
Neural Comput.
Adam S. Charles, Pierre Garrigues, Christopher J. Rozell
2012 J jnl
Low Power Sparse Approximation on Reconfigurable Analog Hardware.
IEEE J. Emerg. Sel. Topics Circuits Syst.
Samuel A. Shapero, Adam S. Charles, Christopher J. Rozell, Paul E. Hasler
2012 — conf
The Restricted Isometry Property for Echo State Networks with applications to sequence memory capacity.
SSP
Han Lun Yap, Adam S. Charles, Christopher J. Rozell
2011 Misc conf
Estimation and dynamic updating of time-varying signals with sparse variations.
ICASSP
Muhammad Salman Asif, Adam S. Charles, Justin K. Romberg, Christopher J. Rozell
2011 J jnl
Learning Sparse Codes for Hyperspectral Imagery.
IEEE J. Sel. Top. Signal Process.
Adam S. Charles, Bruno A. Olshausen, Christopher J. Rozell
2011 Misc conf
Sparsity penalties in dynamical system estimation.
CISS
Adam S. Charles, Muhammad Salman Asif, Justin K. Romberg, Christopher J. Rozell