BACK TO INDEX

Publications of G. Russo

Articles in journal or book chapters

  1. V. Centorrino, F. Bullo, and G. Russo. Similarity Matching Networks: Hebbian Learning and Convergence over Multiple Time Scales. Neural Computation, 38:725-764, 2026. Keyword(s): Neural Networks, Theoretical Neuroscience. [bibtex-entry]
  2. V. Centorrino, F. Rossi, F. Bullo, and G. Russo. Proximal Gradient Dynamics and Feedback Control for Equality-Constrained Composite Optimization. European Journal of Control, pp 101615, 2026. [bibtex-entry]
  3. A. Davydov, V. Centorrino, A. Gokhale, G. Russo, and F. Bullo. Time-Varying Convex Optimization: A Contraction and Equilibrium Tracking Approach. IEEE Transactions on Automatic Control, 70(11):7446-7460, 2025. Keyword(s): Contraction Theory. [bibtex-entry]
  4. F. Rossi, V. Centorrino, F. Bullo, and G. Russo. Neural Policy Composition from Free Energy Minimization. Technical Report, 2025. Note: ArXiv:2512.04745. Keyword(s): Neural Networks. [bibtex-entry]
  5. V. Centorrino, F. Bullo, and G. Russo. Modelling and Contractivity of Neural-Synaptic Networks with Hebbian Learning. Automatica, 164:111636, 2024. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]
  6. V. Centorrino, A. Davydov, A. Gokhale, G. Russo, and F. Bullo. On Weakly Contracting Dynamics for Convex Optimization. IEEE Control Systems Letters, 8:1745-1750, 2024. Keyword(s): Contraction Theory. [bibtex-entry]
  7. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Positive Competitive Networks for Sparse Reconstruction. Neural Computation, 36(6):1163–1197, 2024. Keyword(s): Contraction Theory, Neural Networks, Theoretical Neuroscience. [bibtex-entry]
  8. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Euclidean Contractivity of Neural Networks with Symmetric Weights. IEEE Control Systems Letters, 7:1724-1729, 2023. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]

Conference articles

  1. V. Centorrino, F. Rossi, F. Bullo, and G. Russo. Proximal Gradient Dynamics and Feedback Control for Equality-Constrained Composite Optimization. In European Control Conference, Reykjavík, Iceland, July 2026. Note: To appear. [bibtex-entry]
  2. F. Bullo, S. Coogan, E. Dall'Anese, I. R. Manchester, and G. Russo. Advances in Contraction Theory for Robust Optimization, Control, and Neural Computation. In IEEE Conf. on Decision and Control, Rio de Janeiro, Brazil, 2025. [bibtex-entry]
  3. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Biologically Plausible Neural Networks for Sparse Reconstruction: A Normative Framework. In Workshop “Mathematics for Artificial Intelligence and Machine Learning”, Milan, Italy, january 2024. Note: Oral Presentation. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]
  4. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Towards a Top/Down Normative Framework for a Biologically Plausible Explanation of Neural Circuits: Application to Sparse Reconstruction Problems. In 5th International Convention on the Mathematics of Neuroscience and AI, Rome, Italy, May 2024. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]
  5. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Contractivity of Symmetric Neural Networks for Non-negative Sparse Approximation. In CCS/Italy 2023 Italian Regional Conference on Complex Systems, Naples, Italy, october 2023. Note: Poster Presentation. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]
  6. V. Centorrino, F. Bullo, and G. Russo. Contraction Analysis of Hopfield Neural Networks with Hebbian Learning. In IEEE Conf. on Decision and Control, Cancun, Mexico, December 2022. PDF Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]

BACK TO INDEX