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Publications of year 2024
Books and proceedings
  1. F. Bullo. Contraction Theory for Dynamical Systems. Kindle Direct Publishing, 1.2 edition, 2024. ISBN: 979-8836646806. 
    @Book{ fb:24-ctds,
author = {F. Bullo},
title = {Contraction Theory for Dynamical Systems},
year = 2024,
edition = {{1.2}},
publisher = {Kindle Direct Publishing},
isbn = {979-8836646806},
isbn-hardocver= {979-8333395283},
pdf = {https://fbullo.github.io/ctds},
oldurl = {http://motion.me.ucsb.edu/book-ctds} 
}


  2. F. Bullo. Lectures on Network Systems. Kindle Direct Publishing, 1.7 edition, April 2024. ISBN: 978-1986425643. 
    @Book{ fb:24-lns,
author = {F. Bullo},
title = {Lectures on Network Systems},
month = apr,
year = 2024,
edition = {{1.7}},
publisher = {Kindle Direct Publishing},
pdf = {https://fbullo.github.io/lns},
oldpdf = {http://motion.me.ucsb.edu/book-lns},
oldurl = {http://motion.me.ucsb.edu/book-lns},
isbn = {978-1986425643},
isbnhardcover2024={979-8324736446} 
}


Thesis
  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. 
    @PhDThesis{ vc:24,
author = {V. Centorrino},
title = {Contracting Dynamics for Biologically Plausible Neural Networks and Optimization},
school = {Modeling and Engineering Risk and Complexity, Scuola Superiore Meridionale},
year = 2024,
month = dec,
pdf = {http://motion.me.ucsb.edu/pdf/phd-vc-dec24.pdf},
keywords = {Contraction Theory, Network Systems, Machine Learning, Neural Networks} 
}


  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. 
    @PhDThesis{ sj:24,
author = {S. Jaffe},
title = {Dynamical Systems and Neural Networks: From Implicit Models to Memory Retrieval},
school = {Computer Science Department, University of California at Santa Barbara},
year = 2024,
month = sep,
pdf = {http://motion.me.ucsb.edu/pdf/phd-sj-sep24.pdf},
keywords = {Contraction Theory, Network Systems, Machine Learning} 
}


Articles in journal, book chapters
  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. 
    @Article{ sb-gb-fb-sz:24m,
author = {S. Betteti and G. Baggio and F. Bullo and S. Zampieri},
title = {Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval},
doi = {10.48550/arXiv.2411.07388},
note = {Working Paper},
year = 2024 
}


  2. S. Betteti, G. Baggio, F. Bullo, and S. Zampieri. Stimulus-Driven Dynamics for Robust Memory Retrieval in Hopfield Networks. 2024. Note: Working Paper. 
    @Article{ sb-gb-fb-sz:23k,
author = {S. Betteti and G. Baggio and F. Bullo and S. Zampieri},
title = {Stimulus-Driven Dynamics for Robust Memory Retrieval in {Hopfield} Networks},
note = {Working Paper},
year = 2024,
doi = {10.48550/arXiv.2411.05849} 
}


  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. 
    @Article{ vc-fb-gr:22k,
author = {V. Centorrino and F. Bullo and G. Russo},
title = {Modelling and Contractivity of Neural-Synaptic Networks with {Hebbian} Learning},
year = 2024,
volume = 164,
pages = 111636,
journal = automatica,
nodoi = {10.48550/arXiv.2204.05382},
doi = {10.1016/j.automatica.2024.111636},
keywords = {Contraction Theory, Neural Networks} 
}


  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. 
    @Article{ vc-ad-ag-gr-fb:24a,
author = {V. Centorrino and A. Davydov and A. Gokhale and G. Russo and F. Bullo},
title = {On Weakly Contracting Dynamics for Convex Optimization},
year = 2024,
volume = 8,
pages = {1745-1750},
journal = lcss,
keywords = {Contraction Theory, Neural Networks},
doi = {10.1109/LCSYS.2024.3414348},
arxivdoi = {10.48550/arXiv.2403.07572} 
}


  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. 
    @Article{ vc-ag-ad-gr-fb:23a,
author = {V. Centorrino and A. Gokhale and A. Davydov and G. Russo and F. Bullo},
title = {Positive Competitive Networks for Sparse Reconstruction},
year = 2024,
journal = {Neural Computation},
volume = 36,
number = 6,
pages = {1163–1197},
nodoi = {10.48550/arXiv.2311.03821},
doi = {10.1162/neco_a_01657},
keywords = {Contraction Theory, Neural Networks} 
}


  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. 
    @Article{ lc-fb-eda:23g,
author = {L. Cothren and F. Bullo and E. {Dall'Anese}},
title = {Online Feedback Optimization and Singular Perturbation via Contraction Theory},
journal = sicon,
year = 2024,
month = aug,
note = "Submitted",
keywords = {Contraction Theory},
doi = {10.48550/arXiv.2310.07966} 
}


  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. 
    @Article{ od-ro-ebs-ao-fb-mm:22p,
author = {O. Dalin and R. Ofir and E. {Bar~Shalom} and A. Ovseevich and F. Bullo and M. Margaliot},
fullauthor = {Omri Dalin, Ron Ofir, Eyal {Bar~Shalom}, Alexander Ovseevich, R. Ofir and F. Bullo and M. Margaliot},
title = {Verifying $k$-Contraction without Computing $k$-Compounds},
year = 2024,
journal = tac,
volume = 69,
number = 3,
pages = {1492-1506},
doi = {10.1109/TAC.2023.3326058},
keywords = {Contraction Theory},
nodoi = {10.48550/arXiv.2209.01046} 
}


  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. 
    @Article{ ad-fb:24i,
author = {A. Davydov and F. Bullo},
title = {Exponential Stability of Parametric Optimization-Based Controllers via {Lur'e} contractivity},
journal = lcss,
year = 2024,
volume = 8,
pages = {1277-1282},
keywords = {Contraction Theory},
arxivdoi = {10.48550/arXiv.2403.08159},
doi = {10.1109/LCSYS.2024.3408110} 
}


  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. 
    @Article{ ad-fb:24g,
author = {A. Davydov and F. Bullo},
title = {Perspectives on Contractivity in Control, Optimization and Learning},
year = 2024,
journal = lcss,
volume = 8,
pages = {2087-2098},
doi = {10.1109/LCSYS.2024.3436127},
keywords = {Contraction Theory, Neural Networks} 
}


  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. 
    @Article{ ad-sj-avp-fb:23b,
author = {A. Davydov and S. Jafarpour and A. V. Proskurnikov and F. Bullo},
title = {Non-{Euclidean} Monotone Operator Theory and Applications},
journal = jmlr,
year = 2024,
volume = 25,
number = 307,
pages = {1-33},
doi = {10.48550/arXiv.2303.11273},
keywords = {Contraction Theory, Neural Networks} 
}


  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. 
    @Article{ ad-avp-fb:22q,
author = {A. Davydov and A. V. Proskurnikov and F. Bullo},
title = {{Non-Euclidean} Contraction Analysis of Continuous-Time Neural Networks},
journal = tac,
year = 2024,
keywords = {Contraction Theory, Neural Networks},
arxivdoi = {10.48550/arXiv.2110.08298},
doi = {10.1109/TAC.2024.3422217},
note = {To appear} 
}


  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. 
    @Article{ gdp-kds-fb-mev:21m,
author = {G. {De~Pasquale} and K. D. Smith and F. Bullo and M.~E. Valcher},
title = {Dual Seminorms, Ergodic Coefficients, and Semicontraction Theory},
journal = tac,
year = 2024,
volume = 69,
number = 5,
pages = {3040-3053},
doi = {10.1109/TAC.2023.3302788},
keywords = {Contraction Theory},
olddoi = {10.48550/arXiv.2201.03103} 
}


  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. 
    @Article{ gdg-fb-jrm:24p,
author = {G. Diaz-Garcia and F. Bullo and J. R. Marden},
title = {Strategic Coalitions in Networked Contest Games},
journal = tac,
year = 2024,
month = aug,
note = {Submitted} 
}


  14. A. Gokhale, A. Davydov, and F. Bullo. Proximal Gradient Dynamics: Monotonicity, Exponential Convergence, and Applications. IEEE Control Systems Letters, 2024. 
    @Article{ ag-ad-fb:24d,
author = {A. Gokhale and A. Davydov and F. Bullo},
title = {Proximal Gradient Dynamics: {Monotonicity}, Exponential Convergence, and Applications},
journal = lcss,
year = 2024,
doi = {10.48550/arXiv.2409.10664} 
}


  15. Y. John, G. Diaz-Garca, 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. 
    @Article{ yj-gdg-xd-jrm-fb:23q,
author = {Y. John and G. Diaz-Garc\'ia and X. Duan and J. R. Marden and F. Bullo},
title = {A Stochastic Surveillance {Stackelberg} Game: Co-Optimizing Defense Placement and Patrol Strategy},
journal = tac,
year = 2024,
month = feb,
doi = {10.48550/arXiv.2308.14714},
note = {Submitted} 
}


  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. 
    @Article{ wl-js-gw-fb-jc:23e,
title = {Learning Robust Data-based {LQG} Controllers from Noisy Data},
author = {W. Liu and J. Sun and G. Wang and F. Bullo and J. Chen},
year = 2024,
journal = tac,
volume = 69,
number = 12,
pages = {8526-8538},
arxivdoi = {10.48550/arXiv.2305.01417},
doi = {10.1109/TAC.2024.3409749} 
}


  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. 
    @Article{ zm-fb-aga:23r,
author = {Z. Marvi and F. Bullo and A. G. Alleyne},
title = {Control Barrier Proximal Dynamics: {A} Contraction Theoretic Approach for Safety Verification},
journal = lcss,
year = 2024,
volume = 8,
pages = {880-885},
doi = {10.1109/LCSYS.2024.3402188},
olddoi = {10.48550/arXiv.2309.05873} 
}


  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. 
    @Article{ zm-fb-aga:24n,
author = {Z. Marvi and F. Bullo and A. G. Alleyne},
title = {Robust and Exponential Stability in Barrier-Certified Systems via Contracting Piecewise Smooth Dynamics},
journal = lcss,
year = 2024,
nodoi = {10.1109/LCSYS.2024.3402188},
olddoi = {10.48550/arXiv.2309.05873},
note = {To appear} 
}


  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. 
    @Article{ wm-jh-gc-fb-fd:22u,
title = {Convergence, Consensus and Dissensus in the Weighted-Median Opinion Dynamics},
author = {W. Mei and J. M. Hendrickx and G. Chen and F. Bullo and F. Dorfler},
year = 2024,
journal = tac,
volume = 69,
number = 10,
pages = {6700-6714},
olddoi = {10.48550/arXiv.2212.08808},
doi = {10.1109/TAC.2024.3376752} 
}


  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. 
    @Article{ ro-fb-mm:24q,
author = {R. Ofir and F. Bullo and M. Margaliot},
title = {A sufficient condition for 2-contraction of a feedback interconnection},
year = 2024,
journal = tac,
note = {Submitted},
doi = {10.48550/arXiv.2408.12790},
keywords = {Contraction Theory} 
}


  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. 
    @Article{ avp-fb:22n,
author = {A. V. Proskurnikov and F. Bullo},
title = {Regular pairings for non-quadratic {Lyapunov} functions and contraction analysis},
journal = sicon,
year = 2024,
month = sep,
note = {Submitted},
keywords = {Contraction Theory},
doi = {10.48550/arXiv.2408.17350} 
}


  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. 
    @Article{ ry-xd-rz-xh-zs-fb:23h,
author = {R. Yan and X. Duan and R. Zou and X. He and Z. Shi and F. Bullo},
fullauthor = {rui.yan@cs.ox.ac.uk (Rui Yan), xduan@sjtu.edu.cn (Xiaoming Duan), zr20@mails.tsinghua.edu.cn (Rui Zou), hex20@mails.tsinghua.edu.cn (Xin He), szy@mail.tsinghua.edu.cn (Zongying Shi), bullo@ucsb.edu (Francesco Bullo).},
title = {Multiplayer Homicidal Chauffeur Reach-Avoid Games: {A} Pursuit Enclosure Function Approach},
journal = automatica,
note = {To appear},
year = 2024,
doi = {10.48550/arXiv.2311.02389} 
}


  23. W. Ye, F. Bullo, N. E. Friedkin, and A. K. Singh. Computational Models for Human-AI Team Decision Making. 2024. 
    @Article{ wy-fb-nef-aks:22w,
author = {W. Ye and F. Bullo and N. E. Friedkin and A. K. Singh},
title = {Computational Models for Human-{AI} Team Decision Making},
oldtitle = {Modeling Human-{AI} Team Decision Making},
nonote = {Available at \ {http://arxiv.org/abs/2201.02759}},
year = 2024,
doi = {10.48550/arXiv.2201.02759} 
}


Conference articles
  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. 
    @InProceedings{ vc-ag-ad-gr-fb:23a2,
author = {V. Centorrino and A. Gokhale and A. Davydov and G. Russo and F. Bullo},
title = {Biologically Plausible Neural Networks for Sparse Reconstruction: {A} Normative Framework},
year = 2024,
month = january,
address = {Milan, Italy},
note = {Oral Presentation},
booktitle = {Workshop “Mathematics for Artificial Intelligence and Machine Learning”},
keywords = {Contraction Theory, Neural Networks},
oldurl = {https://dec.unibocconi.eu/mathematics-artificial-intelligence-and-machine-learning} 
}


  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. 
    @InProceedings{ vc-ag-ad-gr-fb:23a3,
author = {V. Centorrino and A. Gokhale and A. Davydov and G. Russo and F. Bullo},
title = {Towards a Top/Down Normative Framework for a Biologically Plausible Explanation of Neural Circuits: {Application} to Sparse Reconstruction Problems},
year = 2024,
month = may,
address = {Rome, Italy},
booktitle = {5th International Convention on the Mathematics of Neuroscience and {AI}},
keywords = {Contraction Theory, Neural Networks},
oldurl = {https://www.neuromonster.org} 
}


  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. 
    @InProceedings{ sj-ad-dl-aks-fb:24c,
title = {Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees},
author = {S. Jaffe and A. Davydov and D. Lapsekili and A. K. Singh and F. Bullo},
fullauthor = {Deniz Lapsekili},
doi = {10.48550/arXiv.2402.08090},
year = 2024,
booktitle = neurips 
}


  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. 
    @InProceedings{ yj-ch-gdg-jm-fb:23s,
title = {{RoSSO}: {A} High-Performance Python Package for Robotic Surveillance Strategy Optimization Using {JAX}},
author = {Y. John and C. Hughes and G. Diaz-Garcia and J. Marden and F. Bullo},
booktitle = icra,
address = {Yokohama, Japan},
month = may,
year = 2024,
nodoi = {missing so far},
note = {To appear},
keywords = {Robotic Surveillance},
doi = {10.48550/arXiv.2309.08742} 
}


  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. 
    @InProceedings{ rm-ag-fb-tg:24h,
author = {R. Marjieh and A. Gokhale and F. Bullo and T. Griffiths},
fullauthor = {Raja Marjieh, Anand Gokhale, Francesco Bullo and Tom Griffiths},
title = {Task Allocation in Teams as a Multi-Armed Bandit},
month = jun,
year = 2024,
booktitle = {ACM Collective Intelligence},
note = {Accepted for both poster and oral presentation} 
}



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