School of Mathematical Sciences
Natural and Health Sciences
Advisor: Dr. Judy Walker
This work has been funded by NSF DMS-1951599 (2020 – 2023) and NIH R01 EB022862 (2016 – 2021). Google scholar profile
Curto and K. Morrison. Graph rules for recurrent network dynamics. Under review for Notices of the American Mathematical Society.
Curto, J. Geneson, K. Morrison. Stable fixed points of combinatorial threshold-linear
networks. Available at https://arxiv.org/abs/1909.02947. Under review.
Morrison, A. Degeratu, V. Itskov, C. Curto. Diversity of emergent dynamics in competitive
threshold-linear networks. Available at https://arxiv.org/abs/1605.04463 Under review.
Curto, J.Geneson, K. Morrison. Stable fixed points of combinatorial threshold-linear networks. Available at https://arxiv.org/abs/1909.02947
Bolkema, K. Morrison, J. L. Walker. The Tensor-Like Join: A Graph-Theoretic Approach to Polar Codes.
Curto, C. Langdon, K. Morrison. Robust motifs of threshold‐linear networks.Available athttps://arxiv.org/abs/1902.10270.
Langdon, K. Morrison*, C. Curto*. Combinatorial geometry of threshold-linear networks. (* equal last authors) Available athttps://arxiv.org/abs/2008.01032
Parmelee, J. Londono Alvarez, C. Curto*, K. Morrison*. Sequential attractors in combinatorial threshold-linear networks. SIAM Journal of Applied Dynamical Systems, 21(2), 2022. (* equal last authors)
Egas Santander, S. Ebli, A. Patania, N. Sanderson, F. Burtscher, K. Morrison*, C.
Curto*. Nerve theorems for fixed points of neural networks. In Research in Computational Topology 2, Assoc. Women Math. Ser. 30, E. Gasparovic, V. Robins, and K. Turner, eds., Springer,
Cham, 2022. (* equal last authors)
Parmelee, S. Moore, K. Morrison*, C. Curto*. Core motifs predict dynamic attractors in combinatorial threshold-linear networks. PLOS ONE, 17(3): e0264456, 2022. (* equal last authors)
Curto and K. Morrison. Relating network connectivity to dynamics: opportunities and challenges for theoretical neuroscience. Current Opinion in Neurobiology, Vol 58, 11-20, 2019.
Curto, E. Gross, J. Jeffries, K. Morrison*, Z. Rosen, A. Shiu, N. Youngs. Algebraic signatures of convex and non-convex codes.J. of Pure and Appl. Algebra, Vol. 223, No. 9, 3919-3940, 2019. (* corresponding author)
Curto, J. Geneson, K. Morrison. Fixed points of competitive threshold-linear networks. Neural Computation, Vol 33, No. 1, 94-155, 2019.
Morrison and C. Curto. Predicting neural network dynamics via graphical analysis. Book chapter in Algebraic and Combinatorial Computational Biology. R. Robeva, M. Macaulay (Eds) 2018.
A.M. Burzynski, S.W. Anderson, K. Morrison, M.R. Patrick, T. Orr, W. Thelen, Lava lake thermal pattern classification using self-organizing maps and relationships to eruption processes at Kīlauea Volcano, Hawai'i. Chapter in Field Volcanology: A Tribute to the Distinguished Career of Don Swanson. M.P. Poland, M. O. Garcia, V. E. Camp, A. Grunder (Eds) 2018.
Curto, E. Gross, J. Jeffries, K. Morrison, M. Omar, Z. Rosen, A. Shiu, N. Youngs. What makes a neural code convex? SIAM J. Appl. Algebra Geometry, Vol 1, 222-238, 2017.
Curto, K. Morrison. Pattern completion in threshold-linear networks. Neural Computation, Vol 28, 2825-2852, 2016.
Karakok, K. Morrison, C. Craviotto. Lessons Learned from a Math Teachers’ Circle. Association for Women in Mathematics Series: Mathematics Education, Vol. 7, Jacqueline Dewar et al. (Eds), 2016.
Morrison. Enumeration of Equivalence Classes of Self-Dual Matrix Codes.Advances in Mathematics of Communication. Vol 9, No. 4, 415-436, 2015.
Gluesing-Luerssen, K. Morrison, C. Troha. Cyclic Orbit Codes and Stabilizer Subfields. Advances in Mathematics of Communication. Vol 9, No. 2, 177-197, 2015.
Gluesing-Luerssen, K. Morrison, C. Troha. On the Cardinality and Distance of Cyclic Orbit Codes based on Stabilizer Subfields. Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems. July 7-11, 2014.
Morrison. Equivalence for rank-metric and matrix codes and automorphism groups of Gabidulin codes.IEEE Transactions on Information Theory. Vol 60, Issue 11, pp. 1-12, 2014.
Curto, V. Itskov, K. Morrison, Z. Roth, J. L. Walker. Combinatorial neural codes from a mathematical coding theory perspective. Neural Computation. Vol 25, pp. 1891-1925, 2013.
Hunt, K. Morrison, C. Dabrowski. Spectral Based Methods that Streamline the Search for Failure Scenarios in Large-Scale Distributed Systems.Proceedings of the IASTED International Conference on Applied Simulation and Modeling, June 22-24th, 2011.
Axvig, K. Morrison, E. Psota, D. Dreher, L. C. Pérez, J. L. Walker. Analysis of connections between pseudocodewords. IEEE Transactions on Information Theory. Vol 55, Issue 9, pp. 4099-4107, 2009.
Axvig, K. Morrison, E. Psota, D. Dreher, L. C. Pérez, J. L. Walker. Towards universal cover decoding. In Proceedings of International Symposium on Information Theory and Its Applications. December 2008.
Axvig, K. Morrison, E. Psota, D. Dreher, L. C. Pérez, J. L. Walker. Average min-sum decoding of LDPC codes. In Proceedings of Internat’l Symposium on Turbo Codes and Related Topics. September 2008.