Publications

Submitted / preprints

• LDLE: Low Distortion Local Eigenmaps
  D. Kohli, A. Cloninger and G. Mishne [arXiv]


• Smooth graph learning for functional connectivity estimation
  S. Gao*, X. Xia*, D. Scheinost and G. Mishne
  


• Multi-scale Affinities with Missing Data: Estimation and Applications
  M. Zhang, G. Mishne and E. C. Chi
  


• Provable Robustness by Geometric Regularization of ReLU Networks
  C. Holtz, C. Shi and G. Mishne
  


• Non-linear manifold learning in fMRI uncovers a low-dimensional space of brain dynamics
  S. Gao, G. Mishne and D. Scheinost [biorxiv]


• Automated cellular structure extraction in biological images with applications to calcium imaging data
  G. Mishne, R. R. Coifman, M. Lavzin and J. Schiller
  [bioRxiv]

Journal Publications

• COBRAC: a fast implementation of convex biclustering with compression
  H. Yi, L. Huang, G. Mishne and E. C. Chi
  Bioinformatics, 2021. [code], [website]


• Kernel-based parameter estimation of dynamical systems with unknown observation functions
  O. Lindenbaum*, A. Sagiv*, G. Mishne and R. Talmon Chaos: An Interdisciplinary Journal of Nonlinear Science 31, 043118, 2021. [arXiv]


• Multi-way Graph Signal Processing on Tensors: Integrative analysis of irregular geometries
  J. S. Stanley, E. C. Chi and G. Mishne
  IEEE Signal Processing Magazine, vol. 37, no. 6, pp. 160-173, Nov. 2020. [arXiv]


• Spectral embedding norm: looking deep into the spectrum of the graph Laplacian
  X. Cheng and G. Mishne
  SIAM Journal on Imaging Sciences, 2020, 13(2), 1015–1048. [arXiv]


• Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science
  A. Jaffe, Y. Kluger, G. C. Linderman, G. Mishne and S. Steinerberger
  Journal of Applied Probability, 57(2), 458-476, June 2020. [arXiv]


• The Geometry of Nodal Sets and Outlier Detection
  X. Cheng, G. Mishne and S. Steinerberger
  Journal of Number Theory, Oct. 2017. [code]


• Diffusion Nets
  G. Mishne, U. Shaham, A. Cloninger and I. Cohen
  Applied and Computational Harmonic Analysis, Aug. 2017. [code]


• Data-driven tree transforms and metrics
  G. Mishne, R. Talmon, I. Cohen, Y. Kluger and R. R. Coifman
  IEEE Transactions on Signal and Information Processing over Networks, Aug. 2017. [python] [Matlab]


• Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery
  G. Mishne, R. Talmon, R. Meir, J. Schiller, U. Dubin and R. R. Coifman
  Special Issue of IEEE Journal of Selected Topics in Signal Processing on Advanced Signal Processing in Brain Networks, vol. 10, no. 7, pp. 1238-1253, Oct. 2016. [code]


• Graph-Based Supervised Automatic Target Detection
  G. Mishne, R. Talmon and I. Cohen
  IEEE Trans. Geoscience and Remote Sensing, Vol. 53, Number 5, May 2015, pp. 2738-2754.


• Multiscale Anomaly Detection Using Diffusion Maps
  G. Mishne and I. Cohen
  Special Issue of IEEE Journal of Selected Topics in Signal Processing on Anomalous Pattern Discovery for Spatial, Temporal, Networked, and High-Dimensional Signals, Vol. 7, Number 1, Feb. 2013, pp. 111-123. [code]

Conference Proceedings

• Scalable Algorithms for Convex Clustering
  W. Zhou, H. Yi, G. Mishne and E. C. Chi
  Accepted to IEEE Data Science and Learning Workshop (DSLW-2021).


• Online Adversarial Purification based on Self-supervised Learning
  C. Shi, C. Holtz and G. Mishne
  Accepted to ICLR-2021.


• Poincaré embedding reveals edge-based functional networks of the brain
  S. Gao, G. Mishne and D. Scheinost
  MICCAI-2020, pp. 448-457, Online, October 2020.


• Visualizing the PHATE of Neural Networks
  S. Gigante, A. S. Charles, S. Krishnaswamy and G. Mishne
  NeurIPS 2019, Vancouver, December 2019. [arXiv] [code]


• Co-manifold learning with missing data
  G. Mishne, E. C. Chi, R. R. Coifman
  ICML 2019, Long Beach, CA, June 2019. [arXiv]


• A hierarchical manifold learning framework for high-dimensional brain imaging data
  S. Gao, G. Mishne, D. Scheinost
  IPMI-2019, Hong Kong, June 2019.


• Learning spatially-correlated temporal dictionaries for calcium imaging
  G. Mishne and Adam S. Charles
  IEEE Internat. Conf. Acoust. Speech Signal Process., ICASSP-2019, Brighton, UK, May 2019.


• Hierarchical nonlinear embedding reveals brain states and performance differences during working memory tasks
  S. Gao, G. Mishne, D. Scheinost
  Conference on Cognitive Computational Neuroscience, CCN-2018, Philadelphia, PA, September 2018.


• Iterative diffusion-based anomaly detection
  G. Mishne and I. Cohen
  Proc. 42nd IEEE Internat. Conf. Acoust. Speech Signal Process., ICASSP-2017, New Orleans, USA, March 2017.


• Improving resolution in supervised patch-based target detection
  R. Amit, G. Mishne and R. Talmon
  Proc. 41st IEEE Internat. Conf. Acoust. Speech Signal Process., ICASSP-2016, Shanghai, China, March 2016.


• Multi-Channel Wafer Defect Detection Using Diffusion Maps
  G. Mishne and I. Cohen
  Proc. 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI-2014, Eilat, Israel, 3-5 December 2014.


• Multiscale Anomaly Detection Using Diffusion Maps and Saliency Score
  G. Mishne and I. Cohen
  Proc. 39th IEEE Internat. Conf. Acoust. Speech Signal Process., ICASSP-2014, Florence, Italy, May 4-9, 2014, pp. 2823-2827.

Peer-reviewed Abstracts / Workshop papers

• LDLE: Low Distortion Local Eigenmaps
  D. Kohli, A. Cloninger and G. Mishne
  ICLR 2021 Workshop ICLR Geometrical and Topological Representation Learning


• Multi-session Alignment for Longitudinal Calcium Imaging
  S. Yadav, R. Hattori, E-J. Hwang, A. Ramot, A. Wu, T. Komiyama and G. Mishne,
  accepted to Computational and Systems Neuroscience (COSYNE) 2021


• Embedding Disentangled Dynamics from Behavioral Videos
  C. Shi, S. Levy, M. Lavzin, J. Schiller and G. Mishne,
  accepted to Computational and Systems Neuroscience (COSYNE) 2021


• The PHATE of learning networks
  S. Gigante, A. Charles, S. Krishnaswamy and G. Mishne
  Computational and Systems Neuroscience (COSYNE) 2020


• Hierarchical Tensor Partitioning and Tiling for Learning Coupled Multiscale Neuronal Dynamics
  G. Mishne, H. Benisty, M. Lavzin, S. Levy, R. Talmon, R. Meir, J. Schiller and R. Coifman,
  Computational and Systems Neuroscience (COSYNE) 2020


• Spatially-filtered temporal dictionary learning for calcium imaging analysis
  G. Mishne, N. Cermak, J. Schiller and A. S. Charles
  SPARS 2019


• Graph-filtered temporal dictionary learning for calcium imaging analysis
  G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, C. Brody, D. W. Tank, and A. S. Charles
  Oral presentation at Annual Computational Neuroscience Meeting (CNS*2019)


• Temporal dictionary learning for calcium imaging analysis
  G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, C. Brody, D. W. Tank, and A. S. Charles
  Computational and Systems Neuroscience (COSYNE) 2019


• Local diffusion geometry for automated cellular structure extraction in calcium imaging data
  G. Mishne, R. R. Coifma, M. Lavzin and J. Schiller
  Computational and Systems Neuroscience (COSYNE) 2018