M. Kalia MSc (Manu)

Kalia, M. (2022). Data, models and transitions in computational neuroscience: Bottom-up and top-down approaches. University of Twente. https://doi.org/10.3990/1.9789036554091

Engels, M. , Kalia, M., Rahmati, S., Petersilie, L., Kovermann, P. , van Putten, M. J. A. M., Rose, C. R. , Meijer, H. G. E., Gensch, T., & Fahlke, C. (2021). Glial chloride homeostasis under transient ischemic stress. Frontiers in cellular neuroscience, 15, [735300]. https://doi.org/10.3389/fncel.2021.735300

Kalia, M., Brunton, S. L. , Meijer, H. G. E. , Brune, C., & Kutz, J. N. (2021). Learning normal form autoencoders for data-driven discovery of universal, parameter-dependent governing equations. arXiv.org. https://arxiv.org/abs/2106.05102

Kalia, M. , Meijer, H. G. E. , van Gils, S. A. , van Putten, M. J. A. M., & Rose, C. R. (2021). Ion dynamics at the energy-deprived tripartite synapse. PLoS Computational Biology, 17(6), [e1009019]. https://doi.org/10.1371/journal.pcbi.1009019

Kalia, M., Brunton, S. L. , Meijer, H. G. E. , Brune, C., & Kutz, J. N. (2020). Deep learning of normal form autoencoders for universal, parameter-dependent dynamics. Paper presented at 1st NeurIPS workshop on Interpretable Inductive Biases and Physically Structured Learning. https://inductive-biases.github.io/papers/46.pdf

Kalia, M. , Meijer, H. G. E. , van Putten, M. J. A. M., Rose, C. R. , & van Gils, S. A. (2019). The energy deprived tripartite synapse: a biophysical model. Poster session presented at 28th Annual Computational Neuroscience Meeting, CNS 2019, Barcelona, Spain.

Kalia, M. , Kouznetsov, I. A. , & Meijer, H. G. E. (2019). Homoclinic saddle to saddle-focus transitions in 4D systems. Nonlinearity, 32(6), 2024-2054. https://doi.org/10.1088/1361-6544/ab0041