Publications

Peer-reviewed Journal and Conference Papers

  • E. Yezerets, N. Mudrik, and A.S. Charles. Decomposed Linear Dynamical Systems (dLDS) models reveal context-dependent dynamic connectivity in C. elegans. 2024. Submitted biorxiv.
  • R.-H. Wei, O.R. Stanley, A.S. Charles, and K.E. Cullen. Contextual neck muscle control enables flexible head stabilization across locomotion conditions. Submitted. 2024.
  • A.H. Daraie, A.S. Charles, L.A. Sanchez, A. Chandler, M.A. Hays, L. Talley, S.K. Inati, K. Zaghloul, J.L. Hopp, A. Marashly, N.E. Crone, J. Gonzalez-Martinez, J.-Y. Kang, and S.V. Sarma. Seizure detection and localization using spectral entropy of the intracranial EEG network. 2024. Submitted.
  • N. Mudrik, R. Ly, O. Ruebel, and A.S. Charles. CrEIMBO: Cross-ensemble interactions in multi-view brain observations. 2024. Submitted. arxiv.
  • S.S. Koukuntla, J.B. Julian, J.C. Kaminsky, M. Schottdorf, D.W. Tank, C.D. Brody, and A.S. Charles. Discovering shared and private geometry in multi-view data. 2024. Submitted. arxiv
  • J. Xie, L.C. Voinov, N. Mudrik, G. Mishne, and A.S. Charles. Multiway Multislice PHATE: Visualizing hidden dynamics of RNNs through training. 2024. Submitted. arxiv
  • S. Moore*, Z. Wang*, Z. Zhu, R. Sun, A. Lee, A.S. Charles, and K.V. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. 2023. Submitted. *Equal Contribution. biorxiv
  • N. Mudrik, E. Yezerets, Y. Chen, C. J. Rozell, and A.S. Charles. Linocs: Lookahead inference of networked operators for continuous stability. Transactions of Machine Learning Research (TMLR). 2024. pdf. 
  • Y. Chen, N. Mudrik, K.A. Johnsen, S. Alagapan, A.S. Charles, and C.J. Rozell. Probabilistic decomposed linear dynamical systems for robust discovery of latent neural dynamics. Neural Information Processing Systems (NeurIPS). 2024. Accepted arxiv
  • I. Dmitrieva, S. Babkin, and A.S. Charles. realSEUDO for Real-time calcium imaging analysis. Neural Information Processing Systems (NeurIPS). Dec. 2024.. arxiv
  • V. Geadah, G. Barello, D. Greenidge, A.S. Charles and J.W. Pillow. Sparse-coding variational auto-encoders. Neural Computation. Dec. 2024. pdf
  • N. Mudrik, G. Mishne, and A.S. Charles. SiBBlInGS: Similarity-driven building-block inference using graphs across States. International Conference on Machine Learning (ICML). 2024. pdf.
  • N. Mudrik*, Y. Chen*, E. Yezerets, C.J. Rozell, and A.S. Charles. Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics. Journal of Machine Learning Research. 2024. In Press. *Equal Contribution. pdf.
  • C. Lamaitre, A.S. Charles, and S. Sarma. Exploration of a network-based EEG marker for major depressive disorder. Conference of the IEEE Engineering in Medicine and Biology (EMBC), Orlando, FL, USA, 2024
  • J. Stefanowicz, J.S. Choi, K. Wingel, J. Haggerty, A.S. Charles, and B. Pesaran. Widefield super-resolution feature matching of the primate cortical surface enables real-time localization. Conference of the IEEE Engineering in Medicine and Biology (EMBC), Orlando, FL, USA, 2024
  • A. H. Daraie, A.S. Charles, A. Chandler, L. Sanchez, J.-Y. Kang, and S. Sarma. Localizing the seizure onset zone with bayesian learning during ieeg monitoring. Conference of the IEEE Engineering in Medicine and Biology (EMBC), Orlando, FL, USA, 2024
  • C. Bao and A.S. Charles. Comparing spike sorting algorithms on simulated extracellular multi-electrode array recordings. Proc. of the IEEE Bioinformatics and Biomedicine (BIBM), Istambul, Turkey, December 2023.
  • X. Yuan, J.I. Colonell, A. Lebedeva, A.S. Charles+, T.D. Harris+.  Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD. 2023. eLife. Paper biorxiv +Joint senior author
  • G. Mishne, A.S. Charles. Deep and shallow data science for multi-scale optical neuroscience. Photonics West. 2024 arxiv
  • A. El Hady*, D. Takahashi*, R. Sun, T. Boyd-Meredith, Y. Zhang, A.S. Charles+, and C.D. Brody+. Chronic functional ultrasound imaging for cognitive behaviors in freely moving rodents. 2023. Journal of Neuroscience Methods, *Equal contribution, +Joint senior author biorxiv pdf
  • T. Xu, A.R. Graves, G. Coste, R. Huganir, D. Bergles, A.S. Charles+, and J. Sulam+. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice. Nature Methods. 2023.  +Joint senior author biorxiv pdf 
  • Noga Mudrik and A. S. Charles. Multi-lingual DALL-E storytime, IEEE Integrated STEM Education Conference (ISEC), March, 2023 arxiv
  • H. Benisty, A. Song, G. Mishne, and A.S. Charles. Data Processing of Functional Optical Microscopy for Neuroscience. arXiv:2201.03537 NeuroPhotonics. 9(4):041402. 2022. pdf
  • A.S. Charles, N. Cermak, R. Affan, B. Scott, J. Schiller, and G. Mishne. GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging. bioRxiv 2021.05.24.445514 . IEEE Transactions of Signal Processing 31:3509-3524, 2022. IEEE link pdf code
  • J.L. Gauthier, S.A. Koay, E.H. Nieh, D.W. Tank, J.W. Pillow, and A.S. Charles. Detecting and Correcting False Transients in Calcium Imaging. Nature Methods. 19:478-478. 2022. pdf 
  • S.A. Koay, A.S. Charles, S.Y. Thiberge, C.D. Brody, and D.W. Tank. Sequential and efficient neural-population coding of complex task information. Neuron.  2022. link pdf
  • Vogelstein, J.T., Verstynen, T., Kording, K.P., Isik, L., Krakauer, J.W., Etienne-Cummings, R., Ogburn, E.L., Priebe, C.E., Burns, R., Kutten, K. and Knierim, J.J., et al. 2022. Prospective Learning: Back to the Future. arXiv preprint arXiv:2201.07372. 2022. arxiv pdf 
  • A. Song, J.L. Gauthier, J.W. Pillow, D.W. Tank, and A.S. Charles. Neural Anatomy and Optical Microscopy (NAOMi) Simulation for evaluating calcium imaging methods. Journal of Neuroscience Methods 358:109173, 2021. paper link, biorxiv pdf, code, data
  • Q. She, X. Wu, B. Jelfs, A.S. Charles, and R.H.M. Chan. An Efficient and Flexible Spike Train Model via Empirical Bayes. IEEE Transactions of Signal Processing. 69:3236-3251. 2021. pdf
  • A.S. Charles, B. Falk, N. Turner, T.D. Pereira, D. Tward, B.D. Pedigo, J. Chung, R. Burns, S.S. Ghosh, J.M. Kebschull, W. Silversmith, and J.T. Vogelstein. Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics. Annual Review of Neuroscience 43(1):441-464, 2020. pdf
  • J. Choi, K. Kumar, M. Khazali, K. Wingel, M. Choudhury, A.S. Charles, and B. Pesaran. Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield. Neural Information Processing Systems (NeurIPS), Virtual, December 2020. pdf
  • 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. IEEE Signal Processing Letters 27:1120-1124, 2020. *Equal contribution. IEEE Xplore, pdf.
  • S. Gigante, A.S. Charles, S. Krishnaswamy, and G. Mishne. Visualizing the PHATE of Neural Networks. Neural Inormation Processing Systems (NeurIPS), Vancouver, Canada, December 2019.pdf
  • G. Mishne and A.S. Charles. Learning spatially-correlated temporal dictionaries for calcium imaging. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019 (Selected for oral presentation) 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.S. Charles and 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. 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, 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. 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 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
  • 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.
  • 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, 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
  • 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. (Selected for oral presentation) 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. (Nominated for best student paper/Selected for oral presentation) 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

  • N. Mudrik, G. Mishne, and A.S. Charles. Sibblings: Similarity-driven building-block inference using graphs across states. ICML AI for Science Workshop, Vienna, Austria, Jul. 2024
  • N. Mudrik, Y. Chen, E. Yezerets, C.J. Rozell, and A.S. Charles. Decomposed linear dynamical systems (dLDS) for identifying the latent dynamics underlying high-dimensional time-series. ICML Workshop on Geometry-grounded Representation Learning and Generative Modeling, Vienna, Austria, Jul. 2024
  • I. Garwood, J. Choi, K. Wingel, J. Stefanowicz, K. Chiang, A. Dubey, J. Viventi, A.S. Charles, and B. Pesaran. Multiregional neuronal calcium imaging during cortical electrical stimulation. Simian Collective Conference, Pittsburg, PA, USA, Sep. 2024
  • S. Moore, Z. Wang, R. Sun, A. Lee, A.S. Charles, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. Advances and perspectives in Auditory Neuroscience (APAN), Chicago, IL, USA, Oct. 2024
  • Z. Zhu, A.S. Charles, and K. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. Advances and perspectives in Auditory Neuroscience (APAN), Chicago, IL, USA, Oct. 2024
  • M.E. Xie, A. Negrean, L. Kinsey, G. Jaindl, A.S. Charles, K. Podgorski, and K. Svoboda. Measurement of input-output signals in vivo using high-speed two-photon microscopy Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • P. Jiang, A.S. Charles, and M. Aoi. RNN Discovery of linear dynamical systems features. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • A. Estrada, G. Kang, G. Mishne, and A.S. Charles. Fast and accessible morphology-free calcium imaging analysis. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • Z. Zhu, A.S. Charles, and K. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • B. Pesaran, I.C. Garwood, K. Wingel, J. Haggerty, A.S. Charles, J. Choi, and A. Dubey. System and method for calcium imaging and electrophysiology in non-human primates. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • Z. Zhu, A.S. Charles, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual
    behavior. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • A. Rupasinghe, A.S. Charles, and J.W. Pillow. Continuous partitioning of neuronal variability. Society
    of Neuroscience (SfN) Conference, Washington D.C., USA, Oct. 2024
  • N. Mudrik, G. Mishne, and A.S. Charles. Sibblings: Similarity-driven building-block inference using neural graphs across states. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal, March 2024
  • S. Koukuntla, T. Harris, A. S. Charles, and C. Brody. Unsupervised discovery of nonlinear and interpretable communication submanifolds. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal, March 2024
  • A.H. Daraie, A.S. Charles, L.A. Sanchez, L. Talley, J.Y. Kang, and S.V. Sarma. A comprehensive seizure detection, localization and classification tool for epilepsy monitoring. AI Epilepsy Conference, Salt Lake City, Utah, USA, Mar. 2024
  • N. Mudrik, G. Mishne, and A.S. Charles. Exploring temporal and structural variability in neural ensembles across trials and conditions. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023. Selected for Nanosymposium presentation
  • E. Yezerets, N. Mudrik, Y. Chen, C. Rozell, and A.S. Charles. Decomposed linear dynamical systems for C. elegans functional connectivity. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023. Selected for Nanosymposium presentation
  • L. Xiang, P. Kanold, and A.S. Charles. Unsupervised extraction of neural activity motifs encoding stimulus and choice information in mice primary auditory cortex. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • G.I. Coste, A.R. Graves, Z. Chen, T. Li, Y.T. Xu, D.E. Bergles, J. Sulam A.S. Charles, and R.L. Huganir. Tracking plasticity of millions of synapses induced by learning and memory in vivo. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • K. Podgorski, A.S. Charles, D.A. Flickinger, G. Jaindl, A. Negrean, J. Rohde, and M.E. Xie. Secondgeneration scanned line projection microscopy (SLAP2) for in vivo imaging of synaptic input. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • K. Johnsen, N. Cruzado, A.S. Charles, and C.J. Rozell. Enhancing the cleo experiment simulation testbed to support all-optical control, multi-channel optogenetics, and easier integration into data analysis pipelines. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • B. Pesaran, J. Choi, K. Wingel, J. Haggerty, and A.S. Charles. Multiregional calcium imaging of neurons in the non-human primate brain. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • S. Moore, Z. Wang, R. Sun, A. Lee, A. S. Charles, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior during audio-motor learning. Advances and Perspecitves in Auditory Neuroscience (APAN), Washington DC, USA, Nov. 2023
  • Y. Cheng, R. Magnard, C. Drieu, D. Garr, L.A. Castell, A. Langdon, A.S. Charles, D. Lee, and P.H. Janak. Chronic ethanol vapor exposure in adult rats persistently reduces behavioral flexibility in protracted withdrawal. Society of Neuroscience (SfN) Conference, Washington D.C., USA, Nov. 2023
  • A.H. Daraie, L.A. Sanchez, L. Talley, A.S. Charles, J.Y. Kang, and S.V. Sarma. Seizure detection using entropy of source-sink nodal dynamics in the epileptic network. Annual meeting of the American Epilepsy Society (AES), Orlando, Florida, USA, Dec. 2023
  • N. Mudrik, G. Mishne, and A. S. Charles. Studying latent neuronal functional circuits underlying brain activity across task conditions. IEEE EMBS Conference on Neural Engineering (NER), Baltimore, Maryland, USA, April 2023
  • A. H. Daraie, L. Sanchez, K. Gunnarsdottir, J. Yi-Kang, A. S. Charles, and S. Sarma. A patient-specific approach for epileptic seizure prediction by tracking network dynamics using source-sink connectivity. IEEE EMBS Conference on Neural Engineering (NER), Baltimore, Maryland, USA, April 2023
  • E. Yezerets, N. Mudrik, Y. Chen, C. Rozell, and A. S. Charles. Decomposed linear dynamical systems for c. elegans functional connectivity. Computational and Systems Neuroscience (CoSyNe), Montreal, Canada, March 2023
  • I. Dmitrieva, S. Babkin, and A. S. Charles. On-line seudo for real-time cell recognition in calcium imaging. Computational and Systems Neuroscience (CoSyNe), Montreal, Canada, March 2023
  • S. Koukuntla, T. Harris, and A. S. Charles. Automatic spike sorting correction and burst detection for high-density electrophysiological recordings. Computational and Systems Neuroscience (CoSyNe),
    Montreal, Canada, March 2023
  • D. Zoltowski, A. S. Charles, J. Pillow, and S. Keeley. Improved estimation of latent variable models from calcium imaging data. Computational and Systems Neuroscience (CoSyNe), Montreal, Canada, March 2023
  • S. Moore, Z. Wang, R. Sun, A. Lee, A. S. Charles, and K. Kuchibhotla. Revealing sudden transitions from goal-directed to habitual behavior during learning in mice. Computational and Systems
    Neuroscience (CoSyNe), Montreal, Canada, March 2023
  • J. Haggerty, J. Choi, M. W. Choudhury, K. Wingel, B. Pesaran, and A. S. Charles. Mapping and localizing neurons using a robotic multiphoton microscope in NHP. Society for Neuroscience (SfN), San Diego, California, November 2022. Selected for nanosymposium
  • B. Pesaran, A. S. Charles, J. Choi, K. Wingel, J. Haggerty, H. Hafizi, A. Dubey, M. W. Choudhury, and R. Bakhshi. A robotic platform for multiregional calcium imaging in the non-human primate brain. Society for Neuroscience (SfN), San Diego, California, November 2022. Selected for nanosymposium
  • K. Wingel, J. Choi, M. Choudhury, A. S. Charles, H. Hafizi, A. Dubey, R. Bakhshi, and B. Pesaran. Multi-regional functional two photon calcium imaging in an awake behaving rhesus macaque. Society for Neuroscience (SfN), San Diego, California, November 2022
  • X. Yuan, J. Colonell, A. S. Charles, and T. Harris. Neuron tracking with chronic neuropixels 2.0 recordings from mouse visual cortex. Society for Neuroscience (SfN), San Diego, California, November 2022
  • S. Moore, Z. Wang, R. Sun, Z. Zhu, A. Lee, A. S. Charles, and K. Kuchibhotla. Sudden transition from goal-directed to habitual behavior during sensorimotor learning in mice. Society for Neuroscience (SfN) Conference, San Diego, California, November 2022
  • T. Xu, A. Graves, G. Coste, R. Huganir, D. Bergles, A. S. Charles, and J. Sulam. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice. Society for Neuroscience (SfN) Conference, San Diego, California, November 2022
  • D. Day, J. Gauthier, D. Tank, and A.S. Charles. Classifying transients in calcium imaging via convolutional neural nets. Neuromatch Acadamy 4.0, November 2021
  • T. Xu, A. Graves, G. Coste, R. Huganir, D. Bergles, A.S. Charles, and J. Sulam. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice. Neuromatch Acadamy 4.0, November 2021
  • J. Choi, M. Khazali, A.S. Charles, and B. Pesaran. Multi-scale measurements of primate motor cortex during free reaching. Brain Initiative Investigators Meeting, June 2021
  • S. Keeley*, D. Zoltowski*, A.S. Charles, J.W. Pillow. Improved estimation of neural encoding models from calcium imaging data. Brain Initiative Investigator’s Meeting, June, 2020. *Equal contribution 
  • A.S. Charles, N. Cermak, J. Shiller, and G. Mishne. Calcium imaging analysis with graph filtered temporal dictionary learning. Society for Neuroscience (SfN), Chicago, Illinois, October 2019
  • A.S. Charles and J. W. Pillow. Continuous-time partitioning of neural variability. Society for Neuroscience (SfN) Conference, Chicago, Illinois, October 2019
  • G. Mishne, N. Cermak, J. Shiller, and A.S. Charles. Spatially-filtered temporal dictionary learning for calcium imaging analysis. Signal Processing with Adaptive Sparse Structured Representations (SPARS), Toulouse, France, June 2019
  • G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, D.W. Tank, and A.S. Charles. Graph-filtered temporal dictionary learning for calcium imaging analysis. Computational Neuroscience Meeting (CNS), Barcelona, Spain, July 2019 (Selected for oral presentation)
  • J.L. Gauthier, S.A. Koay, E. Nieh, D.W. Tank, J.W. Pillow, and A.S. Charles. Sparse-coding variational auto-encoders. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal, July 2019
  • G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, D.W. Tank, and A.S. Charles. Temporal dictionary learning for calcium imaging analysis. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal, July 2019
  • G. Barello, A.S. Charles, and J.W. Pillow. Sparse-coding variational auto-encoders. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal, July 2019
  • 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 falsetransients 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. 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. Signal Processing with Adaptive Sparse Structured Representations (SPARS) Lisbon, Portugal, June 2017.
  • A.S. Charles, D. Yin, and C.J. Rozell. Compression of multiple input streams into recursive neural networks. Signal Processing with Adaptive Sparse Structured Representations (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. Signal Processing with Adaptive Sparse Structured Representations (SPARS)  Lisbon, Portugal, June 2017.
  • A.S. Charles and J.W. Pillow. Continuous-time partitioning of binned spike counts. Computational and Systems Neuroscience (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. Computational and Systems Neuroscience (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. Computational and Systems Neuroscience (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. Neural Information Processing Systems (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. Neural Information Processing Systems (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. Signal Processing with Adaptive Sparse Structured Representations (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. Biologically Inspired Cognitive Architectures (BICA). Cambridge, Massachusetts, November 2014.
  • A.S. Charles, C.J. Rozell, and N. Tufillaro, Sparsity based spectral super-resolution and applications to water color. IEEE International Geoscience and REmote Sensing Symposium (IGARSS) Quebec, Canada, May 2014. pdf
  • A.S. Charles and C.J. Rozell. Stochastic filtering via reweighted l1. Signal Processing with Adaptive Sparse Structured Representations (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. Signal Processing with Adaptive Sparse Structured Representations (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, Banf, Canada, July 2012
  • A.S. 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.S. Charles. Spectral super-resolution of hyperspectral images. SIAM Conference on Imaging Science, Philadelphia, PA, May 2012
  • C.J. Rozell and A.S. 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. Computational and Systems Neuroscience (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. Signal Processing with Adaptive Sparse Structured Representations (SPARS), Edinburgh, Scotland UK, 2011 (Selected for oral presentation) pdf, slides

Other publications

  • A.S. Charles, Interpreting Deep Learning: The Machine Learning Rorschach Test? Society for Industrial and Applied Mathematics (SIAM) News, Jul. 2018. link, extended 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