1. F. Bullo and S. L. Smith. Lectures on Robotic Planning and Kinematics. Unpublished Manuscript, 2022. [bibtex-entry]

1. 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]

1. O. Askarisichani, F. Bullo, N. E. Friedkin, and A. K. Singh. Predictive Models for Human-AI Nexus in Group Decision-Making. Annals of the New York Academy of Sciences, 1514(1):70-81, 2022. [bibtex-entry]



2. C. Beck, F. Bullo, G. Como, K. Drakopoulos, D. H. Nguyen, C. Nowzari, V. M. Preciado, and S. Sundaram. Special Issue on Mathematical Modeling, Analysis, and Control of Epidemics. SIAM Journal on Control and Optimization, 60(2):Si-Sii, 2022. [bibtex-entry]



3. P. Cisneros-Velarde and F. Bullo. Multi-group SIS Epidemics with Simplicial and Higher-Order Interactions. IEEE Transactions on Control of Network Systems, 9(2):695-705, 2022. [bibtex-entry]



4. 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]



5. 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]



6. 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]



7. R. Delabays, S. Jafarpour, and F. Bullo. Multistabilities and Anomalies in Oscillator Models of Lossy Power Grids. Nature Communications, 13:5238, 2022. [bibtex-entry]



8. 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]



9. S. Jafarpour, E. Y. Huang, K. D. Smith, and F. Bullo. Flow and Elastic Networks on the $n$-Torus: Geometry, Analysis and Computation. SIAM Review, 64(1):59-104, 2022. [bibtex-entry]



10. S. Jafarpour, V. Purba, S. V. Dhople, B. B. Johnson, and F. Bullo. Singular Perturbation and Small-signal Stability for Inverter Networks. IEEE Transactions on Control of Network Systems, 9(2):979-992, 2022. [bibtex-entry]



11. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol. IEEE Transactions on Automatic Control, 67(8):3879-3891, 2022. [bibtex-entry]



12. W. Mei, F. Bullo, G. Chen, J. M. Hendrickx, and F. Dorfler. Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of the Weighted-Median Mechanism. Physical Review Research, 4(2):023213, 2022. [bibtex-entry]



13. 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]



14. K. D. Smith, S. Jafarpour, and F. Bullo. Transient Stability of Droop-Controlled Inverter Networks with Operating Constraints. IEEE Transactions on Automatic Control, 67(2):633-645, 2022. [bibtex-entry]



15. K. D. Smith, S. Jafarpour, A. Swami, and F. Bullo. Topology Inference with Multivariate Cumulants: The Möbius Inference Algorithm. IEEE/ACM Transactions on Networking, 30(5):2102-2116, 2022. [bibtex-entry]



16. Y. Tian, P. Jia, A. Mirtabatabaei, L. Wang, N. E. Friedkin, and F. Bullo. Social Power Evolution in Influence Networks with Stubborn Individuals. IEEE Transactions on Automatic Control, 67(2):574-588, 2022. [bibtex-entry]



17. R. Yan, X. Duan, Z. Shi, Y. Zhong, and F. Bullo. Matching-Based Capture Strategies for 3D Heterogeneous Multiplayer Reach-Avoid Differential Games. Automatica, 140:110207, 2022. [bibtex-entry]



18. R. Yan, X. Duan, Z. Shi, Y. Zhong, J. R. Marden, and F. Bullo. Policy Evaluation and Seeking for Multi-Agent Reinforcement Learning via Best Response. IEEE Transactions on Automatic Control, 67(4):1898-1913, 2022. [bibtex-entry]

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]

1. S. Mohagheghi, J. Ma, and F. Bullo. Stable and Efficient Structures in Multigroup Network Formation. Technical report, May 2022. [bibtex-entry]

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. K. D. Smith. High-Order Tomography, 2022. [bibtex-entry]



3. W. Ye, F. Bullo, N. E. Friedkin, and A. K. Singh. Modeling Human-AI Team Decision Making, 2022. Note: Available at http://arxiv.org/abs/2201.02759. [bibtex-entry]

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