1. F. Seccamonte. Bilevel Optimization in Learning and Control with Applications to Network Flow Estimation. PhD thesis, Mechanical Engineering Department, University of California at Santa Barbara, September 2023. Keyword(s): Contraction Theory, Network Systems, Power Networks. [bibtex-entry]

1. 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]



2. G. Chen, W. Su, W. Mei, and F. Bullo. Convergence of the Heterogeneous Deffuant-Weisbuch Model: A Complete Proof and Some Extensions. IEEE Transactions on Automatic Control, February 2023. Note: To appear. [bibtex-entry]



3. J. Cheng, G. Chen, W. Mei, and F. Bullo. Multidimensional Opinion Dynamics with Heterogeneous Bounded Confidences and Random Interactions. Automatica, December 2023. Note: To appear. [bibtex-entry]



4. P. Cisneros-Velarde and F. Bullo. Distributed Wasserstein Barycenters via Displacement Interpolation. IEEE Transactions on Control of Network Systems, 10(2):785-795, 2023. [bibtex-entry]



5. M. Coraggio, S. Jafarpour, F. Bullo, and M. di Bernardo. Minimax Flow over Acyclic Networks: Distributed Algorithms and Microgrid Application. IEEE Transactions on Control of Network Systems, 10(2):937-946, 2023. [bibtex-entry]



6. 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, June 2023. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



7. A. Davydov, S. Jafarpour, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Monotone Operator Theory and Applications. Journal of Machine Learning Research, June 2023. Note: To appear. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]



8. R. Delabays and F. Bullo. Semicontraction and Synchronization of Kuramoto-Sakaguchi Oscillator Networks. IEEE Control Systems Letters, 7:1566-1571, 2023. Keyword(s): Contraction Theory, Oscillator Networks. [bibtex-entry]



9. G. Diaz-Garcìa, F. Bullo, and J. R. Marden. Distributed Markov chain-based Strategies for Multi-Agent Robotic Surveillance. IEEE Control Systems Letters, 7:2527-2532, 2023. [bibtex-entry]



10. A. Gokhale, A. Davydov, and F. Bullo. Contractivity of Distributed Optimization and Nash Seeking Dynamics. IEEE Control Systems Letters, 7:3896-3901, 2023. [bibtex-entry]



11. E. Y. Huang, D. Paccagnan, W. Mei, and F. Bullo. Assign and Appraise: Achieving Optimal Performance in Collaborative Teams. IEEE Transactions on Automatic Control, 68(3):1614-1627, 2023. [bibtex-entry]



12. S. Jafarpour, A. Davydov, and F. Bullo. Non-Euclidean Contraction Theory for Monotone and Positive Systems. IEEE Transactions on Automatic Control, 68(9):5653-5660, 2023. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]



13. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Data-Driven Resilient Model Predictive Control under Denial-of-Service. IEEE Transactions on Automatic Control, 68(8):4722-4737, 2023. [bibtex-entry]



14. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Data-Driven Self-triggered Control via Trajectory Prediction. IEEE Transactions on Automatic Control, 68(11):6951-6958, 2023. [bibtex-entry]



15. 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, 2023. Note: To appear. [bibtex-entry]



16. A. V. Proskurnikov, A. Davydov, and F. Bullo. The Yakubovich S-Lemma Revisited: Stability and Contractivity in Non-Euclidean Norms. SIAM Journal on Control and Optimization, 61(4):1955-1978, 2023. Keyword(s): Contraction Theory. [bibtex-entry]



17. C. Ravazzi, F. Bullo, and F. Dabbene. Unveiling oligarchy in influence networks from partial information. IEEE Transactions on Control of Network Systems, 10(3):1279-1290, 2023. [bibtex-entry]



18. K. D. Smith and F. Bullo. Contractivity of the Method of Successive Approximations for Optimal Control. IEEE Control Systems Letters, 7:919-924, 2023. Keyword(s): Contraction Theory. [bibtex-entry]



19. K. D. Smith and F. Bullo. Convex Optimization of the Basic Reproduction Number. IEEE Transactions on Automatic Control, 68(7):4398-4404, 2023. [bibtex-entry]



20. Y. Tian, L. Wang, and F. Bullo. How Social Influence affects the Wisdom of Crowds in Influence Networks. SIAM Journal on Control and Optimization, 61(4):2334-2357, 2023. [bibtex-entry]

1. 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]



2. A. Davydov, S. Jaffe, A. K. Singh, and F. Bullo. Retrieving $k$-Nearest Memories with Modern Hopfield Networks. In 2023 NEURIPS Workshop on Associative Memory and Hopfield Networks, December 2023. [bibtex-entry]



3. G. Diaz-Garcìa, F. Bullo, and J. R. Marden. Beyond the Enemy-of-my-Enemy Alliances: Coalitions in Networked Contest Games. In IEEE Conf. on Decision and Control, Singapore, December 2023. [bibtex-entry]



4. S. Jaffe, A. K. Singh, and F. Bullo. IDKM: Memory Efficient Neural Network Quantization via Implicit Differentiable $k$-Means. In 2023 ICLR Workshop on Sparsity in Neural Networks, May 2023. Keyword(s): Neural Networks. [bibtex-entry]



5. F. Seccamonte, A. K. Singh, and F. Bullo. Inference of Infrastructure Network Flows via Physics-Inspired Implicit Neural Networks. In IEEE Conf. on Control Technology and Applications, Bridgetown, Barbados, August 2023. Keyword(s): Neural Networks. [bibtex-entry]

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