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Adam S. Charles
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Publications
- 2025
- [c18]Noga Mudrik, Ryan Ly, Oliver Rübel, Adam Shabti Charles:
CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations. ICLR 2025 - 2024
- [j14]Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles:
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics. J. Mach. Learn. Res. 25: 59:1-59:44 (2024) - [j12]Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher John Rozell, Adam Shabti Charles:
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability. Trans. Mach. Learn. Res. 2024 (2024) - [c16]Noga Mudrik, Gal Mishne, Adam S. Charles:
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States. ICML 2024 - [c15]Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam Alagapan, Adam S. Charles, Christopher Rozell:
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics. NeurIPS 2024 - [i13]Gal Mishne, Adam S. Charles:
Deep and shallow data science for multi-scale optical neuroscience. CoRR abs/2402.08811 (2024) - [i12]Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher Rozell, Adam S. Charles:
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability. CoRR abs/2404.18267 (2024) - [i11]Jiancheng Xie, Lou C. Kohler Voinov, Noga Mudrik, Gal Mishne, Adam S. Charles:
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training. CoRR abs/2406.01969 (2024) - [i9]Yenho Chen, Noga Mudrik, Kyle A. Johnsen, Sankaraleengam Alagapan, Adam S. Charles, Christopher J. Rozell:
Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics. CoRR abs/2408.16862 (2024) - 2023
- [c13]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:
Prospective Learning: Principled Extrapolation to the Future. CoLLAs 2023: 347-357 - [i8]Noga Mudrik, Gal Mishne, Adam S. Charles:
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States. CoRR abs/2306.04817 (2023) - 2022
- [j11]Adam S. Charles
, Nathan Cermak, Rifqi O. Affan
, Benjamin B. Scott
, Jackie Schiller
, Gal Mishne
:
GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging. IEEE Trans. Image Process. 31: 3509-3524 (2022) - [i7]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:
Prospective Learning: Back to the Future. CoRR abs/2201.07372 (2022) - [i6]Noga Mudrik, Yenho Chen, Eva Yezerets
, Christopher J. Rozell, Adam S. Charles:
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics. CoRR abs/2206.02972 (2022) - [i5]Noga Mudrik, Adam S. Charles:
Multi-Lingual DALL-E Storytime. CoRR abs/2212.11985 (2022) - 2020
- [j9]Nicholas P. Bertrand, Adam S. Charles
, John Lee
, Pavel Dunn, Christopher J. Rozell
:
Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer. IEEE Signal Process. Lett. 27: 1120-1124 (2020) - 2019
- [c11]Gal Mishne
, Adam S. Charles:
Learning Spatially-correlated Temporal Dictionaries for Calcium Imaging. ICASSP 2019: 1065-1069 - [c10]Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne:
Visualizing the PHATE of Neural Networks. NeurIPS 2019: 1840-1851 - [i4]Scott Gigante
, Adam S. Charles, Smita Krishnaswamy, Gal Mishne:
Visualizing the PHATE of Neural Networks. CoRR abs/1908.02831 (2019) - 2018
- [c9]Nicholas P. Bertrand, John Lee, Adam S. Charles, Pavel Dunn, Christopher J. Rozell:
Sparse Dynamic Filtering via Earth Mover's Distance Regularization. ICASSP 2018: 4334-4338 - 2017
- [j7]Adam S. Charles, Dong Yin, Christopher J. Rozell:
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. J. Mach. Learn. Res. 18: 7:1-7:37 (2017) - [c8]Adam S. Charles, Nicholas P. Bertrand, John Lee, Christopher J. Rozell:
Earth-Mover's distance as a tracking regularizer. CAMSAP 2017: 1-5 - 2016
- [j6]Adam S. Charles
, Aurele Balavoine, Christopher J. Rozell:
Dynamic Filtering of Time-Varying Sparse Signals via ℓ1 Minimization. IEEE Trans. Signal Process. 64(21): 5644-5656 (2016) - [i2]Adam S. Charles, Dong Yin, Christopher J. Rozell:
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. CoRR abs/1605.08346 (2016) - 2014
- [j5]Adam S. Charles, Christopher J. Rozell:
Spectral Superresolution of Hyperspectral Imagery Using Reweighted ℓ1 Spatial Filtering. IEEE Geosci. Remote. Sens. Lett. 11(3): 602-606 (2014) - [j4]Adam S. Charles, Han Lun Yap, Christopher J. Rozell
:
Short-Term Memory Capacity in Networks via the Restricted Isometry Property. Neural Comput. 26(6): 1198-1235 (2014) - [c6]Adam S. Charles, Christopher J. Rozell:
Convergence of basis pursuit de-noising with dynamic filtering. GlobalSIP 2014: 374-378 - [c5]Adam S. Charles, Dong Yin, Christopher J. Rozell:
Can random linear networks store multiple long input streams? GlobalSIP 2014: 379-383 - 2013
- [c4]Adam S. Charles, Christopher J. Rozell:
Dynamic filtering of sparse signals using reweighted ℓ1. ICASSP 2013: 6451-6455 - [i1]Adam S. Charles, Han Lun Yap, Christopher J. Rozell:
Short Term Memory Capacity in Networks via the Restricted Isometry Property. CoRR abs/1307.7970 (2013) - 2012
- [j3]Samuel A. Shapero, Adam S. Charles, Christopher J. Rozell, Paul E. Hasler:
Low Power Sparse Approximation on Reconfigurable Analog Hardware. IEEE J. Emerg. Sel. Topics Circuits Syst. 2(3): 530-541 (2012) - [j2]Adam S. Charles, Pierre Garrigues, Christopher J. Rozell
:
A Common Network Architecture Efficiently Implements a Variety of Sparsity-Based Inference Problems. Neural Comput. 24(12): 3317-3339 (2012) - [c3]Han Lun Yap, Adam S. Charles, Christopher J. Rozell:
The Restricted Isometry Property for Echo State Networks with applications to sequence memory capacity. SSP 2012: 580-583 - 2011
- [j1]Adam S. Charles, Bruno A. Olshausen, Christopher J. Rozell:
Learning Sparse Codes for Hyperspectral Imagery. IEEE J. Sel. Top. Signal Process. 5(5): 963-978 (2011) - [c2]Adam S. Charles, Muhammad Salman Asif
, Justin K. Romberg, Christopher J. Rozell:
Sparsity penalties in dynamical system estimation. CISS 2011: 1-6 - [c1]Muhammad Salman Asif
, Adam S. Charles, Justin K. Romberg, Christopher J. Rozell:
Estimation and dynamic updating of time-varying signals with sparse variations. ICASSP 2011: 3908-3911

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last updated on 2025-07-06 19:38 CEST by the dblp team
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