1. F. Bullo. Contraction Theory for Dynamical Systems. Kindle Direct Publishing, 1.2 edition, 2024. ISBN: 979-8836646806. [bibtex-entry]



2. F. Bullo. Lectures on Network Systems. Kindle Direct Publishing, 1.7 edition, April 2024. ISBN: 978-1986425643. [bibtex-entry]

1. V. Centorrino. Contracting Dynamics for Biologically Plausible Neural Networks and Optimization. PhD thesis, Modeling and Engineering Risk and Complexity, Scuola Superiore Meridionale, December 2024. Keyword(s): Contraction Theory, Network Systems, Machine Learning, Neural Networks. [bibtex-entry]



2. S. Jaffe. Dynamical Systems and Neural Networks: From Implicit Models to Memory Retrieval. PhD thesis, Computer Science Department, University of California at Santa Barbara, September 2024. Keyword(s): Contraction Theory, Network Systems, Machine Learning. [bibtex-entry]

1. S. Betteti, G. Baggio, F. Bullo, and S. Zampieri. Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval. 2024. Note: Working Paper. [bibtex-entry]



2. S. Betteti, G. Baggio, F. Bullo, and S. Zampieri. Stimulus-Driven Dynamics for Robust Memory Retrieval in Hopfield Networks. 2024. Note: Working Paper. [bibtex-entry]



3. 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]



4. 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, Neural Networks. [bibtex-entry]



5. 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. [bibtex-entry]



6. L. Cothren, F. Bullo, and E. Dall'Anese. Online Feedback Optimization and Singular Perturbation via Contraction Theory. SIAM Journal on Control and Optimization, August 2024. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



7. O. Dalin, R. Ofir, E. Bar Shalom, A. Ovseevich, F. Bullo, and M. Margaliot. Verifying $k$-Contraction without Computing $k$-Compounds. IEEE Transactions on Automatic Control, 69(3):1492-1506, 2024. Keyword(s): Contraction Theory. [bibtex-entry]



8. A. Davydov and F. Bullo. Exponential Stability of Parametric Optimization-Based Controllers via Lur'e contractivity. IEEE Control Systems Letters, 8:1277-1282, 2024. Keyword(s): Contraction Theory. [bibtex-entry]



9. A. Davydov and F. Bullo. Perspectives on Contractivity in Control, Optimization and Learning. IEEE Control Systems Letters, 8:2087-2098, 2024. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]



10. A. Davydov, S. Jafarpour, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Monotone Operator Theory and Applications. Journal of Machine Learning Research, 25(307):1-33, 2024. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]



11. A. Davydov, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Contraction Analysis of Continuous-Time Neural Networks. IEEE Transactions on Automatic Control, 2024. Note: To appear. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]



12. G. De Pasquale, K. D. Smith, F. Bullo, and M. E. Valcher. Dual Seminorms, Ergodic Coefficients, and Semicontraction Theory. IEEE Transactions on Automatic Control, 69(5):3040-3053, 2024. Keyword(s): Contraction Theory. [bibtex-entry]



13. G. Diaz-Garcia, F. Bullo, and J. R. Marden. Strategic Coalitions in Networked Contest Games. IEEE Transactions on Automatic Control, August 2024. Note: Submitted. [bibtex-entry]



14. A. Gokhale, A. Davydov, and F. Bullo. Proximal Gradient Dynamics: Monotonicity, Exponential Convergence, and Applications. IEEE Control Systems Letters, 2024. [bibtex-entry]



15. Y. John, G. Diaz-Garcìa, X. Duan, J. R. Marden, and F. Bullo. A Stochastic Surveillance Stackelberg Game: Co-Optimizing Defense Placement and Patrol Strategy. IEEE Transactions on Automatic Control, February 2024. Note: Submitted. [bibtex-entry]



16. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Learning Robust Data-based LQG Controllers from Noisy Data. IEEE Transactions on Automatic Control, 69(12):8526-8538, 2024. [bibtex-entry]



17. Z. Marvi, F. Bullo, and A. G. Alleyne. Control Barrier Proximal Dynamics: A Contraction Theoretic Approach for Safety Verification. IEEE Control Systems Letters, 8:880-885, 2024. [bibtex-entry]



18. Z. Marvi, F. Bullo, and A. G. Alleyne. Robust and Exponential Stability in Barrier-Certified Systems via Contracting Piecewise Smooth Dynamics. IEEE Control Systems Letters, 2024. Note: To appear. [bibtex-entry]



19. W. Mei, J. M. Hendrickx, G. Chen, F. Bullo, and F. Dorfler. Convergence, Consensus and Dissensus in the Weighted-Median Opinion Dynamics. IEEE Transactions on Automatic Control, 69(10):6700-6714, 2024. [bibtex-entry]



20. R. Ofir, F. Bullo, and M. Margaliot. A sufficient condition for 2-contraction of a feedback interconnection. IEEE Transactions on Automatic Control, 2024. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



21. A. V. Proskurnikov and F. Bullo. Regular pairings for non-quadratic Lyapunov functions and contraction analysis. SIAM Journal on Control and Optimization, September 2024. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



22. R. Yan, X. Duan, R. Zou, X. He, Z. Shi, and F. Bullo. Multiplayer Homicidal Chauffeur Reach-Avoid Games: A Pursuit Enclosure Function Approach. Automatica, 2024. Note: To appear. [bibtex-entry]



23. W. Ye, F. Bullo, N. E. Friedkin, and A. K. Singh. Computational Models for Human-AI Team Decision Making. 2024. [bibtex-entry]

1. 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]



2. 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]



3. S. Jaffe, A. Davydov, D. Lapsekili, A. K. Singh, and F. Bullo. Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees. In Advances in Neural Information Processing Systems, 2024. [bibtex-entry]



4. Y. John, C. Hughes, G. Diaz-Garcia, J. Marden, and F. Bullo. RoSSO: A High-Performance Python Package for Robotic Surveillance Strategy Optimization Using JAX. In IEEE Int. Conf. on Robotics and Automation, Yokohama, Japan, May 2024. Note: To appear. Keyword(s): Robotic Surveillance. [bibtex-entry]



5. R. Marjieh, A. Gokhale, F. Bullo, and T. Griffiths. Task Allocation in Teams as a Multi-Armed Bandit. In ACM Collective Intelligence, June 2024. Note: Accepted for both poster and oral presentation. [bibtex-entry]

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