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Publications of year 2024
Books and proceedings
  1. 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} 
}


Articles in journal, book chapters
  1. 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} 
}


  2. V. Centorrino, A. Davydov, A. Gokhale, G. Russo, and F. Bullo. On Weakly Contracting Dynamics for Convex Optimization. IEEE Control Systems Letters, March 2024. Note: Submitted. 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,
month = mar,
journal = lcss,
note = {Submitted},
keywords = {Contraction Theory, Neural Networks},
doi = {10.48550/arXiv.2403.07572} 
}


  3. V. Centorrino, A. Gokhale, A. Davydov, G. Russo, and F. Bullo. Positive Competitive Networks for Sparse Reconstruction. Neural Computation, January 2024. Note: To appear. 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,
month = jan,
journal = {Neural Computation},
note = {To appear},
doi = {10.48550/arXiv.2311.03821},
keywords = {Contraction Theory, Neural Networks} 
}


  4. 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} 
}


  5. A. Davydov and F. Bullo. Exponential Stability of Parametric Optimization-Based Controllers via Lur'e contractivity. IEEE Control Systems Letters, 2024. Note: Submitted. 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,
note = {Submitted},
keywords = {Contraction Theory},
doi = {10.48550/arXiv.2403.08159},
nononononononovolume=7,
nopages = {3896-3901},
nodoi = {10.1109/LCSYS.2023.3341987} 
}


  6. A. Davydov and F. Bullo. Perspectives on Contractivity in Control, Optimization and Learning. IEEE Control Systems Letters, April 2024. Note: Submitted. 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,
month = apr,
journal = lcss,
note = {Submitted},
nodoi = {10.48550/arXiv.2311.03821},
keywords = {Contraction Theory, Neural Networks} 
}


  7. 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. Note: To appear. 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},
note = {To appear},
keywords = {Contraction Theory},
olddoi = {10.48550/arXiv.2201.03103} 
}


  8. Z. Marvi, F. Bullo, and A. G. Alleyne. Control Barrier Proximal Dynamics: A Contraction Theoretic Approach for Safety Verification. IEEE Control Systems Letters, 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,
nodoi = {10.1109/LCSYS.2023.3341987},
olddoi = {10.48550/arXiv.2309.05873} 
}


  9. W. Ye, F. Bullo, N. E. Friedkin, and A. K. Singh. Computational Models for Human-AI Team Decision Making. ACM Transactions on Computer-Human Interaction, 2024. Note: Available at http://arxiv.org/abs/2201.02759. 
    @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},
journal = {ACM Transactions on Computer-Human Interaction},
note = {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. 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} 
}


Miscellaneous
  1. S. Jaffe, A. Davydov, D. Lapsekili, A. K. Singh, and F. Bullo. Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees, 2024. 
    @Misc{ 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},
arxivurl = {https://arxiv.org/pdf/2402.08090},
doi = {10.48550/arXiv.2402.08090},
year = 2024 
}



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