| A user’s guide to topological data analysis E Munch Journal of Learning Analytics 4 (2), 47–61-47–61, 2017 | 112 | 2017 |
| Categorified reeb graphs V De Silva, E Munch, A Patel Discrete & Computational Geometry 55 (4), 854-906, 2016 | 106 | 2016 |
| Chatter detection in turning using persistent homology FA Khasawneh, E Munch Mechanical Systems and Signal Processing 70, 527-541, 2016 | 103 | 2016 |
| Probabilistic Fréchet means for time varying persistence diagrams E Munch, K Turner, P Bendich, S Mukherjee, J Mattingly, J Harer Electronic Journal of Statistics 9 (1), 1173-1204, 2015 | 74* | 2015 |
| Convergence between Categorical Representations of Reeb Space and Mapper E Munch, B Wang 32nd International Symposium on Computational Geometry (SoCG 2016) 51, 53:1 …, 2016 | 52 | 2016 |
| Chatter Classification in Turning using Machine Learning and Topological Data Analysis FA Khasawneh, ElizabethMunch, JA Perea 14th IFAC Workshop on Time Delay Systems TDS 2018: Budapest, Hungary, 28–30 …, 2018 | 50 | 2018 |
| Strong Equivalence of the Interleaving and Functional Distortion Metrics for Reeb Graphs U Bauer, E Munch, Y Wang 31st International Symposium on Computational Geometry (SoCG 2015) 34, 461--475, 2015 | 49 | 2015 |
| Applications of persistent homology to time varying systems E Munch Duke University, 2013 | 46 | 2013 |
| Persistent homology of complex networks for dynamic state detection A Myers, E Munch, FA Khasawneh Physical Review E 100 (2), 022314, 2019 | 36 | 2019 |
| Theory of Interleavings on Categories with a Flow V de Silva, E Munch, A Stefanou Theory and Applications of Categories 33 (21), 583-607, 2018 | 36* | 2018 |
| Topological and statistical behavior classifiers for tracking applications P Bendich, SP Chin, J Clark, J Desena, J Harer, E Munch, A Newman, ... IEEE Transactions on Aerospace and Electronic Systems 52 (6), 2644-2661, 2016 | 36 | 2016 |
| Stability determination in turning using persistent homology and time series analysis FA Khasawneh, E Munch ASME International Mechanical Engineering Congress and Exposition 46483 …, 2014 | 23 | 2014 |
| Feature-aided multiple hypothesis tracking using topological and statistical behavior classifiers D Rouse, A Watkins, D Porter, J Harer, P Bendich, N Strawn, E Munch, ... Signal processing, sensor/information fusion, and target recognition XXIV …, 2015 | 21 | 2015 |
| Failure filtrations for fenced sensor networks E Munch, M Shapiro, J Harer The International Journal of Robotics Research 31 (9), 1044-1056, 2012 | 21 | 2012 |
| Approximating continuous functions on persistence diagrams using template functions JA Perea, E Munch, FA Khasawneh arXiv preprint arXiv:1902.07190, 2019 | 20 | 2019 |
| Topological data analysis for true step detection in periodic piecewise constant signals FA Khasawneh, E Munch Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018 | 20 | 2018 |
| Utilizing topological data analysis for studying signals of time-delay systems FA Khasawneh, E Munch Time Delay Systems, 93-106, 2017 | 20 | 2017 |
| The shape of things to come: Topological data analysis and biology, from molecules to organisms EJ Amézquita, MY Quigley, T Ophelders, E Munch, DH Chitwood Developmental Dynamics 249 (7), 816-833, 2020 | 18 | 2020 |
| A structural average of labeled merge trees for uncertainty visualization L Yan, Y Wang, E Munch, E Gasparovic, B Wang IEEE transactions on visualization and computer graphics 26 (1), 832-842, 2019 | 17 | 2019 |
| Intrinsic interleaving distance for merge trees E Gasparovic, E Munch, S Oudot, K Turner, B Wang, Y Wang arXiv preprint arXiv:1908.00063, 2019 | 16 | 2019 |
Firas KhasawnehMichigan State UniversityAdresse e-mail validée de egr.msu.edu
