Other Publications (Thesis/Preprints)
  • A.S. Charles. Interpreting Deep Learning: The Machine Learning Rorschach Test? Society for Insustrial and Applied Mathematics (SIAM) News Jul. 2018. link,pdf
  • M. Shvartsman, N. Sundaram, M.C. Aoi, A.S. Charles, T.C. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. arXiv:1711.03058 Nov. 2017. pdf
  • A.S. Charles. Dynamics and correlations in sparse signal acquisition. PhD thesis, Georgia Institute of Technology, 2015. pdf
  • A.S. Charles. Adjustable Subband Allocation Algorithm for Critically Sampled Subband Adaptive Filters. Master's Thesis The Cooper Union for the Advancement of Science and Art. April 2009 pdf
Journal Articles
  • J.L. Gauthier, S.A. Koay, E.H. Nieh, D.W. Tank, J.W. Pillow A.S. Charles. Detecting and Correcting False Transients in Calcium Imaging . Submitted 2018.pdf
  • G. Barello, A.S. Charles and J.W. Pillow. Sparse-coding variational auto-encoders. Submitted 2018. pdf .
  • A.S. Charles and C.J. Rozell. Learning dictionaries of dynamics for sparse signal tracking. Submitted 2018.
  • N.P. Bertrand*, A.S. Charles*, J. Lee*, P.B. Dunn, and C.J. Rozell. Efficient tracking of sparse signals via an Earth mover's distance regularizer. Submitted 2018. *Equal contribution. pdf.
  • Q. She, B, Jelfs, A.S. Charles, and R.H.M. Chan. Network modeling of short over-dispersed spike-counts: A hierarchical parametric empirical bayes framework. Submitted 2018. pdf.
  • A.S. Charles*, M. Park*, J.P. Weller, G.D. Horwitz, and J.W. Pillow. Dethroning the Fano Factor: a flexible, model-based approach to partitioning neural variability. Neural Computation 30(4):1012-1045 2018. *Joint first author. pdf. code.
  • A. Song*, A.S. Charles*, S.A. Koay, J.L. Gauthier, S.Y. Thiberge, J.W. Pillow, and D.W. Tank. Volumetric Two-Photon Imaging of Neurons Using Spectroscopy (vTwINS). Nature Methods 14(4):420-426, Apr. 2017. *Joint first author. pdf. code.
  • A.S. Charles, D. Yin, and C.J. Rozell. Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. Journal of Machine Learning Research 18(7):1-37, Jan 2017. pdf.
  • A.S. Charles, A. Balavoine, and C.J. Rozell. Dynamic Filtering of Time-Varying Sparse Signals via l1 Minimization. IEEE Transactions of Signal Processing 2016, 64(21):5644-5656, November 2016. pdf.
  • A.S. Charles, H.L. Yap, and C.J. Rozell. Short term network memory capacity via the restricted isometry property. Neural Computation, 26(6), June, 2014. pdf.
  • A.S. Charles and C.J. Rozell. Spectral superresolution of hyperspectral imagery using reweighted l1 spatial filtering. IEEE Journal of Geoscience and Remote Sensing Letters, 11(3):602-606, March 2014. pdf.
  • A.S. Charles, P. Garrigues, and C.J. Rozell. A common network architecture efficiently implements a variety of sparsity-based inference problems, Neural Computation, 24(12):3317-3339, December 2012. pdf.
  • S. Shapero, A.S. Charles, C.J. Rozell, and P. Hasler. Low power sparse approximation on reconfigurable analog hardware. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2(3):530-541, September 2012. Special Issue on Circuits, Systems and Algorithms for Compressive Sensing. pdf.
  • A.S. Charles, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral images. IEEE Journal of Selected Topics in Signal Processing, 5(5):963-978, September 2011. pdf. code
Conference Papers
  • A.S. Charles, J.W. Pillow. Additive continuous-time joint partitioning of neural variability. Proceedings of the Conference on Cognitive Computational Neuroscience (CCN), Philadelphia, PA, USA, September 2018. pdf.
  • A.S. Charles, H.L. Yap, D. Lin and C.J. Rozell. Short-term sequence memory: Compressive effects of recurrent network dynamics. Proceedings of the Conference on Cognitive Computational Neuroscience (CCN), Philadelphia, PA, USA, September 2018. pdf.
  • N.P. Bertrand, J. Lee, A.S. Charles, P. Dunn, and C.J. Rozell. Sparse dynamic filtering via earth mover’s distance regularization. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Alberta, Canada, April 2018 pdf.
  • M. Shvartsman, N. Sudaram, M.C. Aoi, A.S. Charles, T. L. Wilke, and J. D. Cohen. Matrix-variate models for fMRI analysis. The International Conference on Artificial Intelligence and Statistics (AISTATS), Playa Blanca, Lanzarote, Canary Islands, April 2018. pdf(arxiv), pdf (MLR).
  • A.S. Charles, N.P. Bertrand, J. Lee, and C.J. Rozell. Earth-mover’s distance as a tracking regulaizer. Proceedings the CAMSAP, Curacao, Dutch Antilles, December 2017. pdf
  • A.S. Charles, A. Song, S.A. Koay, D.W. Tank, and J.W. Pillow. Stochastic filtering of two-photon imaging using reweighted `l1. Proceedings of the ICASSP New Orleans, Louisiana, March 2017.
  • A.S. Charles and C.J. Rozell, Convergence of basis pursuit de-noising with dynamic filtering. Proceedings of the GlobalSIP Atlanta, Georgia, November 2014. pdf
  • A.S. Charles, Y. Dong and C.J. Rozell, Can random linear networks store multiple long input streams?. Proceedings of the GlobalSIP Atlanta, Georgia, November 2014. pdf
  • A.S. Charles and C.J. Rozell, Dynamic filtering of sparse signals using reweighted l1. Proceedings of the ICASSP Vancouver, Canada, May 2013. pdf
  • A.S. Charles, A. Ahmed, A. Joshi, S. Conover, C. Turnes, and M.A. Davenport, Cleaning up toxic waste: Removing nefarious contributions to recommendation systems. Proceedings of the ICASSP Vancouver, Canada, May 2013. pdf
  • H.L. Yap, A.S. Charles, and C.J. Rozell, The restricted isometry property for echo state networks with applications to sequence memory capacity. Statistical Signal Processing Workshop Ann Arbor, Michigan, August 2012. pdf
  • A.S. Charles, M.S. Asif, J. Romberg, and C.J. Rozell, Sparsity penalties in dynamical system estimation. Proceedings of the CISS Baltimore, Maryland, March 2011. pdf
  • M.S. Asif, A.S. Charles, J. Romberg and C.J. Rozell, Estimation and dynamic updating of time-varying signals with sparse variations. Proceedings of the ICASSP, Prague, Czech Republic, May 2011. pdf
  • A.S. Charles, A.A. Kressner and C.J. Rozell, Causal sparse decompositions of audio signals. Proceedings of the IEEE Signal Processing (DSP) Workshop, Sedona, AZ, January 2011. pdf (Nominated for best student paper)
  • A.S. Charles, B.A. Olshausen and C.J. Rozell. Sparse coding for spectral signatures in hyperspectral images. Proceedings of the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2010 pdf , poster

Conference Abstracts
  • A.S. Charles, H. L. Yap, D. Yin, and C. J. Rozell. Rigorous guarantees on sequence memory capacity in recurrent neural networks using randomized dimensionality reduction. Theoretical Foundation of Deep Learning, Atlanta, Georgia, October 2018
  • J.L. Gauthier, A.S. Charles, D.W. Tank, and J.W. Pillow. Robust identification and removal of false transients in calcium fluorescence imaging data. Society for Neuroscience (SfN), San Diego, California, September 2018
  • M. Shvartsman, N. Sudaram, M.C. Aoi, A.S. Charles, T.L. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. Organization for Human Brain Mapping (OHBM), Singapore, June 2018
  • M. Shvartsman, N. Sudaram, M.C. Aoi, A.S. Charles, T.L. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. Computational and Systems Neuroscience (CoSyNe), Denver, Colorodo, March 2018
  • J. Lee, A.S. Charles, N.P. Bertrand, and C.J. Rozell. An optimal transport tracking regularizer. Neural Information Processing Systems (NIPS) Workshops, Long Beach, California, December 2017
  • M. Shvartsman, N. Sudaram, M.C. Aoi, A.S. Charles, T.L. Wilke, and J.D. Cohen. Matrix-variate models for fMRI analysis. Neural Information Processing Systems (NIPS) Workshops, Long Beach, California, December 2017
  • A. Song, A. S. Charles, S. Y. Thiberge, J. L. Gauther, S. A. Koay, J. W. Pillow, and D. W. Tank. Volumetric two-photon imaging via stereoscopy and two-photon calcium imaging simulator. Emerging Tools for Acquisition and Interpretation of Whole-Brain Functional Data, Ashburn, Virginia, November 2017
  • J.L. Gauthier, A.S. Charles, D.W. Tank, and J.W. Pillow. Robust estimation of calcium transients by modeling contamination. SFN Washington DC., June 2017.
  • A. S. Song, A.S. Charles, D.W. Tank and J.W. Pillow. A two-photon microscopy simulation framework for optimizing optics and benchmarking cell-finding algorithms. SFN Washington DC., June 2017.
  • A.S. Charles, A. Song, S. A. Koay, J.L. Gauthier, S. Y. Thiberge, D.W. Tank, and J.W. Pillow. Adaptive orthogonal basis pursuit for volumetric two-photon microscopy. SPARS Lisbon, Portugal, June 2017.
  • A.S. Charles, D. Yin, and C.J. Rozell. Compression of multiple input streams into recursive neural networks. SPARS Lisbon, Portugal, June 2017.
  • A.S. Charles, J. Lee, N.P. Bertrand, and C.J. Rozell. Dynamic filtering with earth mover's distance regularization. SPARS Lisbon, Portugal, June 2017.
  • A.S. Charles and J.W. Pillow. Continuous-time partitioning of binned spike counts. CoSyNe Salt Lake City, Utah, February 2017.
  • J.L. Gauthier, A.S. Charles, J.W. Pillow, and D.W. Tank. Robust estimation of calcium transients by modeling contamination. CoSyNe Salt Lake City, Utah, February 2017.
  • A. Song, A.S. Charles, J.L. Gauthier, S.A. Koay, D.W. Tank, and J.W. Pillow. Two-photon microscopy simulation for optics optimization and benchmarking. CoSyNe Salt Lake City, Utah, February 2017.
  • A.S. Charles, H.L. Yap, D. Yin, and C.J. Rozell. Short-term sequence memory in recurrent networks. NIPS Workshops Barcelona, Spain, December 2016.
  • N.P. Bertrand, H.L. Yap, A.S. Charles, and C.J. Rozell. Efficient randomized filtering for dimensionality reduction in electrophysiology data. NIPS Workshops Barcelona, Spain, December 2016.
  • A. Song, A.S. Charles, S.Y. Thiberge, J.L. Gauthier, S.A. Koay, J.W. Pillow, and D.W. Tank. Two-photon imaging of neurons using stereoscopy (TwINS). SfN San Diego, California, December 2016.
  • A.S. Charles and C.J. Rozell, Learning a dynamics dictionary for time-varying sparse signals. SPARS Cambridge, United Kingdom, July 2015.
  • A.S. Charles and C.J. Rozell, Robust estimation of sparse time-varying signals. Information Theory and Applications La Jolla, California, February 2015.
  • C.J. Rozell, M. Zhu, A.S. Charles, H.L. Yap, and M. Norko, The role of sparsity in visual perception. BICA Cambridge, Massachusetts, November 2014.
  • A.S. Charles, C.J. Rozell, and N. Tufillaro, Sparsity based spectral super-resolution and applications to water color. IGARSS Quebec, Canada, May 2014. pdf
  • A.S. Charles and C.J. Rozell. Stochastic filtering via reweighted l1. SPARS, Lausanne, Switzerland, July 2013. pdf, poster
  • A.S. Charles, H.L. Yap, and C.J. Rozell. Using compressed sensing to study sequence memory capacity in networked systems. SPARS, Lausanne, Switzerland, July 2013 pdf
  • A.A. Kressner, A.S. Charles, and C.J. Rozell. Causal locally competitive algorithm for the sparse decomposition of audio signals. IEEE Womens Workshop on Communications and Signal Processing, Ban, Canada, July 2012
  • A. Charles, H.L. Yap, , and C.J. Rozell. Short term memory in neural networks via the restricted isometry property. Computational Neuroscience Meeting Workshop on Methods of Information Theory in Computational Neuroscience, Atlanta, GA, July 2012
  • H.L. Yap, A.S. Charles, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. Challenges in Geometry, Analysis and Computation: High-Dimensional Synthesis, Yale University, June 2012 abstract
  • C.J. Rozell and A. Charles. Spectral super-resolution of hyperspectral images. SIAM Conference on Imaging Science, Philadelphia, PA, May 2012
  • C.J. Rozell and A. Charles. Recursive estimation of dynamic signals with sparsity models via re-weighted l1 minimization. Janelia Farm Conference on Machine Learning, Statistical Inference, and Neuroscience, Ashburn, VA, May 2012
  • A.S. Charles, H.L. Yap, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. Janelia Farm Conference on Machine Learning,Statistical Inference and Neuroscience, Ashburn, Virginia, 2012 poster
  • A.S. Charles, H.L. Yap, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. Proceedings of COSYNE, Salt Lake City, Utah, 2012 pdf, poster
  • A.S. Charles, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral images. Duke Workshop on Sensing and Analysis of High-Dimensional Data (SAHD), Durham, NC, July 2011 poster
  • A.S. Charles and C.J. Rozell, A hierarchical re-weighted-l1 approach for dynamic sparse signal estimation. SPARS, Edinburgh, Scotland UK, 2011 pdf, slides