activity
20072026
most citedGeometric methods for optimal sensor design

22 citations · 109 across the 52 of their papers we have counts for

collaborators

55 papers

math.OC2026

Structural stability of systems and cycle covers in random graphs

Mohamed Ali Belabbas

Structural system theory studies which network topologies can sustain a prescribed system property such as controllability or stability. When the topology is itself random, the rel…

cs.LG2026

Privacy Preserving Gossip Learning

Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar

We propose a decentralized privacy-preserving learning algorithm in which each agent holds a single private sample and a shared model. Samples are learned sequentially, and each up…

math.AG2026

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 of $\operatorname{Der}_{\…

cs.LG2025

Control Disturbance Rejection in Neural ODEs

Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar

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…

cs.LG2025

Geometric Foundations of Tuning without Forgetting in Neural ODEs

Erkan Bayram, Mohamed-Ali Belabbas, Tamer Başar

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…

math.OC2025

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…