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Publications about 'Contraction Theory'
Books and proceedings
  1. F. Bullo. Contraction Theory for Dynamical Systems. Kindle Direct Publishing, 1.1 edition, 2023. ISBN: 979-8836646806. [bibtex-entry]


Thesis
  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]


  2. K. D. Smith. Control and Estimation in Network Systems. PhD thesis, Electrical and Computer Engineering Department, University of California at Santa Barbara, December 2022. Keyword(s): Contraction Theory, Network Systems, Power Networks. [bibtex-entry]


Articles in journal, book chapters
  1. 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), 2024. Note: To appear. Keyword(s): Contraction Theory. [bibtex-entry]


  2. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Contractivity of Competitive Neural Networks for Sparse Reconstruction. Technical Report, September 2023. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  3. 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]


  4. L. Cothren, F. Bullo, and E. Dall'Anese. Singular Perturbation via Contraction Theory. IEEE Transactions on Automatic Control, October 2023. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]


  5. A. Davydov, V. Centorrino, A. Gokhale, G. Russo, and F. Bullo. Contracting Dynamics for Time-Varying Convex Optimization. IEEE Transactions on Automatic Control, June 2023. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]


  6. 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: Submitted. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  7. 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]


  8. 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]


  9. 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]


  10. 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]


  11. V. Centorrino, F. Bullo, and G. Russo. Modelling and Contractivity of Neural-Synaptic Networks with Hebbian Learning. Automatica, July 2022. Note: Submitted. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  12. P. Cisneros-Velarde, S. Jafarpour, and F. Bullo. Contraction Theory for Dynamical Systems on Hilbert Spaces. IEEE Transactions on Automatic Control, 67(12):6710-6715, 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  13. P. Cisneros-Velarde, S. Jafarpour, and F. Bullo. Distributed and Time-Varying Primal-Dual Dynamics via Contraction Analysis. IEEE Transactions on Automatic Control, 67(7):3560-3566, 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  14. 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, September 2022. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]


  15. A. Davydov, S. Jafarpour, and F. Bullo. Non-Euclidean Contraction Theory for Robust Nonlinear Stability. IEEE Transactions on Automatic Control, 67(12):6667-6681, 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  16. A. Davydov, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Contraction Analysis of Continuous-Time Neural Networks. IEEE Transactions on Automatic Control, September 2022. Note: Submitted. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  17. S. Jafarpour, P. Cisneros-Velarde, and F. Bullo. Weak and Semi-Contraction for Network Systems and Diffusively-Coupled Oscillators. IEEE Transactions on Automatic Control, 67(3):1285-1300, 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  18. R. Ofir, F. Bullo, and M. Margaliot. Minimum Effort Decentralized Control Design for Contracting Network Systems. IEEE Control Systems Letters, 6:2731-2736, 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  19. J. W. Simpson-Porco and F. Bullo. Contraction Theory on Riemannian Manifolds. Systems & Control Letters, 65:74-80, 2014. Keyword(s): Nonlinear Control, Mechanical Control Systems, Contraction Theory. [bibtex-entry]


Conference articles
  1. 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. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  2. P. Cisneros-Velarde and F. Bullo. A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows. In International Conference on Artificial Intelligence and Statistics, May 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  3. A. Davydov, S. Jafarpour, M. Abate, F. Bullo, and S. Coogan. Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks. In IEEE Conf. on Decision and Control, Cancun, Mexico, 2022. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  4. A. Davydov, S. Jafarpour, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Monotone Operator Theory with Applications to Recurrent Neural Networks. In IEEE Conf. on Decision and Control, Cancun, Mexico, December 2022. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  5. A. Davydov, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Contractivity of Recurrent Neural Networks. In American Control Conference, Atlanta, USA, pages 1527-1534, May 2022. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  6. S. Jafarpour, M. Abate, A. Davydov, F. Bullo, and S. Coogan. Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach. In Learning for Dynamics and Control Conference, June 2022. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


  7. S. Jafarpour, A. Davydov, M. Abate, F. Bullo, and S. Coogan. Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach. In ICML Workshop on Formal Verification of Machine Learning, July 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  8. K. D. Smith, F. Seccamonte, A. Swami, and F. Bullo. Physics-Informed Implicit Representations of Equilibrium Network Flows. In Advances in Neural Information Processing Systems, November 2022. Keyword(s): Contraction Theory. [bibtex-entry]


  9. F. Bullo, P. Cisneros-Velarde, A. Davydov, and S. Jafarpour. From Contraction Theory to Fixed Point Algorithms on Riemannian and non-Euclidean Spaces. In IEEE Conf. on Decision and Control, December 2021. Keyword(s): Contraction Theory. [bibtex-entry]


  10. S. Jafarpour, A. Davydov, A. V. Proskurnikov, and F. Bullo. Robust Implicit Networks via Non-Euclidean Contractions. In Advances in Neural Information Processing Systems, December 2021. Keyword(s): Contraction Theory, Neural Networks. [bibtex-entry]


Miscellaneous
  1. G. De Pasquale, K. D. Smith, F. Bullo, and M. E. Valcher. Dual Seminorms, Ergodic Coefficients, and Semicontraction Theory, 2022. Note: Available at http://arxiv.org/abs/2201.03103. Keyword(s): Contraction Theory. [bibtex-entry]


  2. S. Jafarpour, P. Cisneros-Velarde, and F. Bullo. Weak and Semi-Contraction Theory with Application to Network Systems, 2020. Note: ArXiv e-print. Keyword(s): Contraction Theory. [bibtex-entry]



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