More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability, Ilia Ilmer, Alexey Ovchinnikov, Gleb Pogudin, Pedro Soto, (2022), arXiv:2204.01623
Obtaining weights for Gröbner basis computation in parameter identifiability problems, Maria Bessonov, Ilia Ilmer, Tatiana Konstantinova, Alexey Ovchinnikov, Gleb Pogudin, Pedro Soto, in review, arxiv:2202.06297;
Lightweight Projective Derivative Codes for Compressed Asynchronous Gradient Descent Pedro Soto, Ilia Ilmer, Haibin Guan, & Jun Li, International Conference on Machine Learning (ICML), 20444-20458 (2022), arXiv:2201.12990;
Maple application for structural identifiability analysis of ODE models, Ilia Ilmer, Alexey Ovchinnikov, Gleb Pogudin, (2021), ACM Communications in Computer Algebra 55 (2), 49-53, link;
Web-based Structural Identifiability Analyzer, Ilia Ilmer, Alexey Ovchinnikov, Gleb Pogudin, International Conference on Computational Methods in Systems Biology, pp. 254-265. Springer, Cham, 2021, arxiv:2106.15066;
On the interplay of harvesting and various diffusion strategies for spatially heterogeneous populations, Elena Braverman, Ilia Ilmer, Journal of Theoretical Biology, Vol 466, 2019, pp 106-118
Tutorials
Parameter Identifiability in ODE Models, tutorial for ModelingToolkit.jl