9 papers
Rigidity for Lie algebras of locally finite derivations
Mohamed Ali Belabbas
Let be a finitely generated commutative algebra over a field of characteristic zero. We prove that every finitely generated Lie subalgebra $L\subseteq\operatorname{…
Control Disturbance Rejection in Neural ODEs
Erkan Bayram, Mohamed-Ali Belabbas, Tamer BaÅar
In this paper, we propose an iterative training algorithm for Neural ODEs that provides models resilient to control (parameter) disturbances. The method builds on our earlier work…
Geometric Foundations of Tuning without Forgetting in Neural ODEs
Erkan Bayram, Mohamed-Ali Belabbas, Tamer BaÅar
In our earlier work, we introduced the principle of Tuning without Forgetting (TwF) for sequential training of neural ODEs, where training samples are added iteratively and paramet…
Interpretable Gradient Descent for Kalman Gain
M. A. Belabbas, A. Olshevsky
We derive a decomposition for the gradient of the innovation loss with respect to the filter gain in a linear time-invariant system, decomposing as a product of an observability Gr…
On the invariance of super-linearization under polynomial automorphisms
Anmol Harshana, Mohamed-Ali Belabbas
We prove that the super-linearizability of polynomial systems is preserved by all currently known classes of polynomial automorphisms of . We then establish connections betwe…
Constructing Stochastic Matrices for Weighted Averaging in Gossip Networks
Erkan Bayram, Mohamed-Ali Belabbas
The convergence of the gossip process has been extensively studied; however, algorithms that generate a set of stochastic matrices, the infinite product of which converges to a ran…