Granger-causality meets causal inference in graphical models: Learning networks via non-invasive observations. - Mihaela Dimovska; Donatello Materassi (CDC, 2017)

A brief explanation of the issue of faithfulness and link orientation in network reconstruction. - Mihaela Dimovska; Donatello Materassi (ACC, 2019)

Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks. - Mihaela Dimovska; Travis Johnston; Catherine D. Schuman; J. Parker Mitchell; Thomas E. Potok (UEMCON, 2019)

A Novel Pruning Method for Convolutional Neural Networks Based off Identifying Critical Filters. - Mihaela Dimovska; Travis Johnston (PEARC, 2019)

An algorithm for reconstruction of triangle-free linear dynamic networks with verification of correctness. - Mihaela Dimovska; Donatello Materassi (CoRR, 2020)

A Control Theoretic Look at Granger Causality: Extending Topology Reconstruction to Networks With Direct Feedthroughs. - Mihaela Dimovska; Donatello Materassi (IEEE Trans. Autom. Control., 2021)

Granger-Faithfulness and Link Orientation in Network Reconstruction. - Mihaela Dimovska; Donatello Materassi (IEEE Trans. Control. Netw. Syst., 2022)