Adam S. Charles

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 21

Top Topics

Empirical Bayes

Top Venues

IEEE Trans. Signal Process.

Publications

Jiancheng Xie, Lou C. Kohler Voinov, Noga Mudrik, Gal Mishne, Adam S. Charles
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training. CoRR (2024)
Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher Rozell, Adam S. Charles
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability. CoRR (2024)
Gal Mishne, Adam S. Charles
Deep and shallow data science for multi-scale optical neuroscience. CoRR (2024)
Noga Mudrik, Gal Mishne, Adam S. Charles
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States. CoRR (2023)
Noga Mudrik, Adam S. Charles
Multi-Lingual DALL-E Storytime. CoRR (2022)
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 (2022)
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 (2022)
Qi She, Xiaoli Wu, Beth Jelfs, Adam S. Charles, Rosa H. M. Chan
An Efficient and Flexible Spike Train Model Via Empirical Bayes. IEEE Trans. Signal Process. 69 (2021)
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 (2020)
John S. Choi, Krishan Kumar, Mohammad Khazali, Katie Wingel, Mahdi Choudhury, Adam S. Charles, Bijan Pesaran
Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield. NeurIPS (2020)
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
Visualizing the PHATE of Neural Networks. CoRR (2019)
Gal Mishne, Adam S. Charles
Learning Spatially-correlated Temporal Dictionaries for Calcium Imaging. ICASSP (2019)
Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
Visualizing the PHATE of Neural Networks. NeurIPS (2019)
Nicholas P. Bertrand, John Lee, Adam S. Charles, Pavel Dunn, Christopher J. Rozell
Sparse Dynamic Filtering via Earth Mover's Distance Regularization. ICASSP (2018)
Adam S. Charles, Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow
Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability. Neural Comput. 30 (4) (2018)
Adam S. Charles
Interpreting Deep Learning: The Machine Learning Rorschach Test? CoRR (2018)
Adam S. Charles, Alexander Song, Sue Ann Koay, David W. Tank, Jonathan W. Pillow
Stochastic filtering of two-photon imaging using reweighted ℓ1. ICASSP (2017)
Adam S. Charles, Dong Yin, Christopher J. Rozell
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. J. Mach. Learn. Res. 18 (2017)
Adam S. Charles, Nicholas P. Bertrand, John Lee, Christopher J. Rozell
Earth-Mover's distance as a tracking regularizer. CAMSAP (2017)
Adam S. Charles, Dong Yin, Christopher J. Rozell
Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. CoRR (2016)
Adam S. Charles, Aurele Balavoine, Christopher J. Rozell
Minimization. IEEE Trans. Signal Process. 64 (21) (2016)
Adam S. Charles, Han Lun Yap, Christopher J. Rozell
Short-Term Memory Capacity in Networks via the Restricted Isometry Property. Neural Comput. 26 (6) (2014)
Adam S. Charles, Christopher J. Rozell
Convergence of basis pursuit de-noising with dynamic filtering. GlobalSIP (2014)
Adam S. Charles, Dong Yin, Christopher J. Rozell
Can random linear networks store multiple long input streams? GlobalSIP (2014)
Adam S. Charles, Christopher J. Rozell
Spatial Filtering. IEEE Geosci. Remote. Sens. Lett. 11 (3) (2014)
Adam S. Charles, Han Lun Yap, Christopher J. Rozell
Short Term Memory Capacity in Networks via the Restricted Isometry Property. CoRR (2013)
Adam S. Charles, Christopher J. Rozell
Dynamic filtering of sparse signals using reweighted ℓ1. ICASSP (2013)
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) (2012)
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) (2012)
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)
Adam S. Charles, Muhammad Salman Asif, Justin K. Romberg, Christopher J. Rozell
Sparsity penalties in dynamical system estimation. CISS (2011)
Adam S. Charles, Bruno A. Olshausen, Christopher J. Rozell
Learning Sparse Codes for Hyperspectral Imagery. IEEE J. Sel. Top. Signal Process. 5 (5) (2011)
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)