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Publications of year 2022
Books and proceedings
  1. F. Bullo. Contraction Theory for Dynamical Systems. Kindle Direct Publishing, 1.0 edition, June 2022. ISBN: 979-8836646806.
    @Book{ fb-ctds:22,
    author = {F. Bullo},
    title = {Contraction Theory for Dynamical Systems},
    year = 2022,
    month = jun,
    edition = {{1.0}},
    publisher = {Kindle Direct Publishing},
    isbn = {979-8836646806} 
    }
    


  2. F. Bullo. Contraction Theory for Nonlinear Networks. Lecture Notes, 0.7 edition, April 2022.
    @Book{ fb:22-ctnn,
    author = {F. Bullo},
    title = {Contraction Theory for Nonlinear Networks},
    month = apr,
    year = 2022,
    edition = {{0.7}},
    publisher = {Lecture Notes} 
    }
    


  3. F. Bullo. Lectures on Network Systems. Kindle Direct Publishing, 1.6 edition, January 2022. ISBN: 978-1986425643.
    @Book{ fb:22,
    author = {F. Bullo},
    title = {Lectures on Network Systems},
    month = jan,
    year = 2022,
    edition = {{1.6}},
    publisher = {Kindle Direct Publishing},
    pdf = {https://ucsb.box.com/v/book-lns},
    isbn = {978-1986425643} 
    }
    


  4. F. Bullo and S. L. Smith. Lectures on Robotic Planning and Kinematics. Unpublished Manuscript (under contract with SIAM), 2022.
    @Book{ fb-sls:22,
    author = {F. Bullo and S. L. Smith},
    title = {Lectures on Robotic Planning and Kinematics},
    year = 2022,
    publisher = {Unpublished Manuscript (under contract with SIAM)},
    nonote = {To appear},
    pdf = {http://motion.me.ucsb.edu/book-lrpk} 
    }
    


Articles in journal, book chapters
  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, 2022.
    @Article{ oa-fb-nef-aks:21h,
    author = {O. Askarisichani and F. Bullo and N. E. Friedkin and A. K. Singh},
    title = {Predictive Models for Human-{AI} Nexus in Group Decision-Making},
    journal = {Annals of the New York Academy of Sciences},
    year = 2022,
    doi = {10.1111/nyas.14783},
    nonote = {https://en.wikipedia.org/wiki/Annals_of_the_New_York_Academy_of_Sciences} 
    }
    


  2. O. Askarisichani, E. Y. Huang, K. S. Sato, N. E. Friedkin, F. Bullo, and A. K. Singh. Expertise and confidence explain how social influence evolves along intellective tasks. Submitted, 2022. Keyword(s): Social Networks.
    @Article{ oa-eyh-kss-nef-fb-aks:20l,
    author = {O. Askarisichani and E. Y. Huang and K. S. Sato and N. E. Friedkin and F. Bullo and A. K. Singh},
    title = {Expertise and confidence explain how social influence evolves along intellective tasks},
    journal = {Submitted},
    year = 2022,
    pdf = {http://arxiv.org/pdf/2011.07168},
    newpdf = {http://motion.me.ucsb.edu/pdf/2020l-ahsfbs.pdf},
    keywords = {Social Networks},
    sigstat = {How do individuals become influential within a team and to what extent is influence affected by cognitive biases and heuristics? Predicting social influence has important applications in finance, politics, and any task-oriented teams. We propose machine learning models to predict interpersonal influence in teams using message content, communication times, and individual task performance. We also propose an intuitive cognitive model that tests and validates the hypotheses that expertise, confidence, and psychological cognitive biases drive the formation of social influence. Our findings on groups of human subjects show the proposed models significantly improve the prediction of influence networks compared to baseline algorithms.} 
    }
    


  3. 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.
    @Article{ cb-fb-etal:22b,
    fullauthor = {Carolyn Beck and Francesco Bullo Giacomo Como and Kimon Drakopoulos and Dang H. Nguyen and Cameron Nowzari and Victor M. Preciado and Shreyas Sundaram},
    author = {C. Beck and F. Bullo and G. Como and K. Drakopoulos and D. H. Nguyen and C. Nowzari and V. M. Preciado and S. Sundaram},
    title = {Special Issue on Mathematical Modeling, Analysis, and Control of Epidemics},
    year = 2022,
    volume = 60,
    number = 2,
    pages = {Si-Sii},
    journal = sicon,
    doi = {10.1137/22N975470} 
    }
    


  4. 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.
    @Article{ pcv-fb:20d,
    author = {P. Cisneros-Velarde and F. Bullo},
    title = {Multi-group {SIS} Epidemics with Simplicial and Higher-Order Interactions},
    year = 2022,
    doi = {10.1109/TCNS.2021.3124269},
    journal = tcns,
    volume = 9,
    number = 2,
    pages = {695-705},
    pdf = {https://arxiv.org/pdf/2005.11404.pdf} 
    }
    


  5. P. Cisneros-Velarde, S. Jafarpour, and F. Bullo. Contraction Theory for Dynamical Systems on Hilbert Spaces. IEEE Transactions on Automatic Control, 2022. Note: To appear. Keyword(s): Contraction Theory.
    @Article{ pcv-sj-fb:20c,
    author = {P. Cisneros-Velarde and S. Jafarpour and F. Bullo},
    title = {Contraction Theory for Dynamical Systems on {Hilbert} Spaces},
    journal = tac,
    year = 2022,
    note = {to appear},
    doi = {10.1109/TAC.2021.3133270},
    nofunding = {HDTRA1-19-1-0017},
    pdf = {https://arxiv.org/pdf/2010.01219.pdf},
    keywords = {Contraction Theory} 
    }
    


  6. G. De Pasquale, F. Bullo, and M. E. Valcher. Ergodicity Coefficients Are Induced Matrix Seminorms. Technical Report, 2022.
    @Article{ gdp-fb-mev:21m,
    author = {G. {De~Pasquale} and F. Bullo and M.~E. Valcher},
    title = {Ergodicity Coefficients Are Induced Matrix Seminorms},
    journal = {Technical Report},
    year = 2022,
    nonote = {Submitted},
    pdf = {https://arxiv.org/abs/2201.03103} 
    }
    


  7. R. Delabays, S. Jafarpour, and F. Bullo. Multistability and Paradoxes in Lossy Oscillator Networks. Submitted, February 2022.
    @Article{ rd-sj-fb:22d,
    author = {R. Delabays and S. Jafarpour and F. Bullo},
    title = {Multistability and Paradoxes in Lossy Oscillator Networks},
    journal = {Submitted},
    year = 2022,
    month = feb,
    pdf = {https://arxiv.org/pdf/2202.02439.pdf} 
    }
    


  8. E. Y. Huang, D. Paccagnan, W. Mei, and F. Bullo. Assign and Appraise: Achieving Optimal Performance in Collaborative Teams. IEEE Transactions on Automatic Control, 2022. Note: To appear.
    @Article{ eyh-dp-wm-fb:19h,
    author = {E. Y. Huang and D. Paccagnan and W. Mei and F. Bullo},
    title = {Assign and Appraise: {A}chieving Optimal Performance in Collaborative Teams},
    journal = tac,
    year = 2022,
    doi = {10.1109/TAC.2022.3156879},
    note = {To appear},
    pdf = {https://arxiv.org/pdf/2008.09817.pdf} 
    }
    


  9. 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.
    @Article{ sj-pcv-fb:19q,
    author = {S. Jafarpour and P. Cisneros-Velarde and F. Bullo},
    title = {Weak and Semi-Contraction for Network Systems and Diffusively-Coupled Oscillators},
    journal = tac,
    year = 2022,
    pdf = {http://arxiv.org/pdf/2005.09774},
    doi = {10.1109/TAC.2021.3073096},
    volume = 67,
    number = 3,
    pages = {1285-1300},
    keywords = {Contraction Theory} 
    }
    


  10. 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.
    @Article{ sj-eyh-kds-fb:18j,
    author = {S. Jafarpour and E. Y. Huang and K. D. Smith and F. Bullo},
    oldtitle = {Multistable Synchronous Power Flows: {F}rom Geometry to Analysis and Computation},
    title = {Flow and Elastic Networks on the $n$-Torus: {Geometry,} Analysis and Computation},
    journal = sirev,
    year = 2022,
    volume = 64,
    number = 1,
    doi = {10.1137/18M1242056},
    pages = {59-104},
    pdf = {https://arxiv.org/pdf/1901.11189.pdf} 
    }
    


  11. 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.
    @Article{ sj-vp-svd-bbj-fb:17j,
    author = {S. Jafarpour and V. Purba and S. V. Dhople and B. B. Johnson and F. Bullo},
    title = {Singular Perturbation and Small-signal Stability for Inverter Networks},
    year = 2022,
    journal = tcns,
    doi = {10.1109/TCNS.2021.3084444},
    volume = 9,
    number = 2,
    pages = {979-992},
    pdf = {https://arxiv.org/pdf/1902.02478.pdf},
    abtract = {This paper considers the small-signal stability of electrical networks composed dominantly of three-phase grid-following inverters. We identify a suitable time-scale decomposition for the inverter dynamics and, using singular perturbation theory, we obtain an analytic sufficient condition for the small-signal stability of the network. In contrast to the alternative of performing an eigenvalue analysis of the full-order network dynamics, our analytic sufficient condition has the benefit of reducing computational complexity and yielding insights on the role of network topology and constitution as well as inverter filter and control parameters on small-signal stability. Our numerical analysis for an inverter network with radial topology validates the approach and illustrates that, in a wide parametric regime, our analytic condition coincides with the exact stability threshold.} 
    }
    


  12. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Data-driven Self-triggered Control via Trajectory Prediction. IEEE Transactions on Automatic Control, March 2022. Note: Submitted.
    @Article{ wl-js-gw-fb-jc:22e,
    title = {Data-driven Self-triggered Control via Trajectory Prediction},
    author = {W. Liu and J. Sun and G. Wang and F. Bullo and J. Chen},
    fullauthor = {Wenjie Liu and Jian Sun and Gang Wang and Francesco Bullo and Jie Chen},
    year = 2022,
    month = mar,
    journal = tac,
    note = {Submitted} 
    }
    


  13. 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, 2022. Note: To appear.
    @Article{ wl-js-gw-fb-jc:21a,
    title = {Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol},
    author = {W. Liu and J. Sun and G. Wang and F. Bullo and J. Chen},
    fullauthor = {Wenjie Liu and Jian Sun and Gang Wang and Francesco Bullo and Jie Chen},
    year = 2022,
    journal = tac,
    note = {To appear},
    pdf = {https://arxiv.org/abs/2103.11862},
    doi = {10.1109/TAC.2021.3107145} 
    }
    


  14. 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.
    @Article{ wm-fb-gc-jh-fd:18q,
    title = {Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of the Weighted-Median Mechanism},
    author = {W. Mei and F. Bullo and G. Chen and J. M. Hendrickx and F. Dorfler},
    year = 2022,
    journal = prr,
    doi = {10.1103/physrevresearch.4.023213},
    volume = 4,
    number = 2,
    pages = 023213,
    oldabstract = {Public opinion formation faces unprecedented challenges such as radicalization, echo chambers, and opinion manipulations. Mathematical modeling plays a fundamental role in understanding how social influence shapes individuals' opinions. Although most opinion dynamics models assume that individuals update their opinions by averaging others' opinions, we point out that this taken-for-granted mechanism features a non-negligible unrealistic implication. By resolving the shortcomings of weighted averaging in the framework of cognitive dissonance theory and network games, we derive a new micro-foundation of opinion dynamics, which happens to be the weighted-median mechanism. Empirical validation indicates that the weighted-median mechanism significantly outperforms the weighted-averaging mechanism in predicting individual opinion shifts. Compared with some widely-studied averaging-based models, the weighted-median model, despite its simplicity in form, replicates more realistic features of opinion dynamics, and exhibits richer phase-transition behavior depending on more delicate and robust network structures. Our new model provides an untouched perspective on the study of opinion formation processes and broadens the applicability of opinion dynamics models.} 
    }
    


  15. S. Mohagheghi, J. Ma, and F. Bullo. Stable and Efficient Structures in Multigroup Network Formation. PLoS One, May 2022. Note: Submitted.
    @Article{ sm-jm-fb:19i,
    author = {S. Mohagheghi and J. Ma and F. Bullo},
    title = {Stable and Efficient Structures in Multigroup Network Formation},
    journal = plosone,
    year = 2022,
    month = may,
    note = {Submitted},
    pdf = {https://arxiv.org/pdf/2001.10627.pdf} 
    }
    


  16. 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.
    @Article{ ro-fb-mm:22h,
    author = {R. Ofir and F. Bullo and M. Margaliot},
    title = {Minimum effort decentralized control design for contracting network systems},
    year = 2022,
    volume = 6,
    pages = {2731-2736},
    journal = csl,
    pdf = {https://arxiv.org/pdf/2203.10392.pdf},
    keywords = {Contraction Theory},
    doi = {10.1109/LCSYS.2022.3176196} 
    }
    


  17. C. Ravazzi, F. Bullo, and F. Dabbene. Unveiling oligarchy in influence networks from partial information. IEEE Transactions on Control of Network Systems, February 2022. Note: Submitted.
    @Article{ cr-fb-fd:21b,
    author = {C. Ravazzi and F. Bullo and F. Dabbene},
    title = {Unveiling oligarchy in influence networks from partial information},
    journal = tcns,
    year = 2022,
    month = feb,
    note = {Submitted} 
    }
    


  18. 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.
    @Article{ kds-sj-fb:18f,
    author = {K. D. Smith and S. Jafarpour and F. Bullo},
    title = {Transient Stability of Droop-Controlled Inverter Networks with Operating Constraints},
    journal = tac,
    year = 2022,
    volume = 67,
    number = 2,
    pages = {633-645},
    pdf = {http://arxiv.org/pdf/1907.05532},
    doi = {10.1109/TAC.2021.3053552} 
    }
    


  19. K. D. Smith, S. Jafarpour, A. Swami, and F. Bullo. Topology Inference with Multivariate Cumulants: The Möbius Inference Algorithm. IEEE/ACM Transactions on Networking, 2022. Note: To appear.
    @Article{ kds-sj-fb-as:20e,
    author = {K. D. Smith and S. Jafarpour and A. Swami and F. Bullo},
    title = {Topology Inference with Multivariate Cumulants: {The} {M\"obius} Inference Algorithm},
    journal = {IEEE/ACM Transactions on Networking},
    year = 2022,
    note = {To appear},
    doi = {10.1109/TNET.2022.3164336},
    pdf = {https://arxiv.org/pdf/2005.07880.pdf} 
    }
    


  20. 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.
    @Article{ yt-pj-am-lw-nef-fb:19c,
    author = {Y. Tian and P. Jia and A. Mirtabatabaei and L. Wang and N. E. Friedkin and F. Bullo},
    title = {Social Power Evolution in Influence Networks with Stubborn Individuals},
    journal = tac,
    year = 2022,
    volume = 67,
    number = 2,
    pages = {574-588},
    pdf = {https://arxiv.org/pdf/1901.08727.pdf},
    doi = {10.1109/TAC.2021.3052485} 
    }
    


  21. Y. Tian, L. Wang, and F. Bullo. How Social Influence affects the Wisdom of Crowds in Influence Networks. SIAM Journal on Control and Optimization, 2022. Note: Submitted.
    @Article{ yt-lw-fb:20q,
    author = {Y. Tian and L. Wang and F. Bullo},
    title = {How Social Influence affects the Wisdom of Crowds in Influence Networks},
    journal = sicon,
    year = 2022,
    note = {Submitted} 
    }
    


  22. R. Yan, X. Duan, Z. Shi, Y. Zhong, and F. Bullo. Maximum-Matching Capture Strategies for 3D Heterogeneous Multiplayer Reach-Avoid Games. Automatica, 2022. Note: To appear.
    @Article{ ry-xd-zs-yz-fb:19o,
    author = {R. Yan and X. Duan and Z. Shi and Y. Zhong and F. Bullo},
    title = {Maximum-Matching Capture Strategies for {3D} Heterogeneous Multiplayer Reach-Avoid Games},
    fullauthor = {Rui Yan and Xiaoming Duan and Zongying Shi and Yisheng Zhong and Francesco Bullo},
    journal = automatica,
    note = {To appear},
    year = 2022,
    pdf = {https://arxiv.org/pdf/1909.11881} 
    }
    


  23. 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.
    @Article{ ry-xd-zs-yz-jrm-fb:20g,
    author = {R. Yan and X. Duan and Z. Shi and Y. Zhong and J. R. Marden and F. Bullo},
    fullauthor = {Rui Yan and Xiaoming Duan and Zongying Shi and Yisheng Zhong and Jason R. Marden and Francesco Bullo},
    title = {Policy Evaluation and Seeking for Multi-Agent Reinforcement Learning via Best Response},
    journal = tac,
    doi = {10.1109/TAC.2021.3085171},
    year = 2022,
    volume = 67,
    number = 4,
    pages = {1898-1913},
    pdf = {https://arxiv.org/pdf/2006.09585.pdf} 
    }
    


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, December 2022. Note: Submitted. Keyword(s): Contraction Theory, Neural Networks.
    @InProceedings{ vc-fb-gr:22g,
    author = {V. Centorrino and F. Bullo and G. Russo},
    title = {Contraction Analysis of {Hopfield} Neural Networks with {Hebbian} Learning},
    year = 2022,
    month = dec,
    booktitle = cdc,
    noaddress = {Cancun, Mexico},
    pdf = {http://arxiv.org/abs/2204.05382},
    nodoi = {10.1109/CDC45484.2021.9682883},
    keywords = {Contraction Theory, Neural Networks},
    note = {Submitted} 
    }
    


  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.
    @InProceedings{ pcv-fb:21d,
    author = {P. Cisneros-Velarde and F. Bullo},
    title = {A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows},
    year = 2022,
    month = may,
    booktitle = {International Conference on Artificial Intelligence and Statistics},
    pdf = {https://arxiv.org/pdf/2105.08832.pdf},
    keywords = {Contraction Theory} 
    }
    


  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, 2022. Note: Submitted. Keyword(s): Contraction Theory, Neural Networks.
    @InProceedings{ ad-sj-ma-fb-sc:21z,
    author = {A. Davydov and S. Jafarpour and M. Abate and F. Bullo and S. Coogan},
    title = {Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks},
    year = 2022,
    booktitle = cdc,
    pdf = {https://arxiv.org/abs/2204.00187},
    nodoi = {m},
    keywords = {Contraction Theory, Neural Networks},
    note = {Submitted} 
    }
    


  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, December 2022. Note: Submitted. Keyword(s): Contraction Theory, Neural Networks.
    @InProceedings{ ad-sj-avp-fb:21j,
    author = {A. Davydov and S. Jafarpour and A. V. Proskurnikov and F. Bullo},
    title = {Non-{Euclidean} Monotone Operator Theory with Applications to Recurrent Neural Networks},
    year = 2022,
    month = dec,
    booktitle = cdc,
    noaddress = {Cancun, Mexico},
    pdf = {https://arxiv.org/pdf/2204.01877.pdf},
    nodoi = {10.1109/CDC45484.2021.9682883},
    keywords = {Contraction Theory, Neural Networks},
    note = {Submitted} 
    }
    


  5. A. Davydov, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Contractivity of Recurrent Neural Networks. In American Control Conference, 2022. Note: To appear. Keyword(s): Contraction Theory, Neural Networks.
    @InProceedings{ ad-avp-fb:21k,
    author = {A. Davydov and A. V. Proskurnikov and F. Bullo},
    title = {{Non-Euclidean} Contractivity of Recurrent Neural Networks},
    booktitle = acc,
    noaddress = {Atlanta, GA, USA},
    nomonth = may,
    year = 2022,
    nopages = {265-270},
    nodoi = {10.23919/ACC.2017.7962964},
    note = {To appear},
    keywords = {Contraction Theory, Neural Networks},
    pdf = {https://arxiv.org/abs/2110.08298} 
    }
    


  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. Note: To appear. Keyword(s): Contraction Theory, Neural Networks.
    @InProceedings{ sj-ma-ad-fb-sc:21y,
    author = {S. Jafarpour and M. Abate and A. Davydov and F. Bullo and S. Coogan},
    title = {Robustness Certificates for Implicit Neural Networks: {A} Mixed Monotone Contractive Approach},
    year = 2022,
    month = jun,
    booktitle = l4dc,
    note = {To appear},
    pdf = {http://arxiv.org/abs/2112.05310.pdf},
    keywords = {Contraction Theory, Neural Networks} 
    }
    


  7. F. Seccamonte, A. K. Singh, and F. Bullo. Network Flow Estimation via Graph Neural Networks and Bilevel Optimization. In Advances in Neural Information Processing Systems, May 2022. Note: Submitted.
    @InProceedings{ fs-aks-fb:22j,
    author = {F. Seccamonte and A. K. Singh and F. Bullo},
    title = {Network Flow Estimation via Graph Neural Networks and Bilevel Optimization},
    year = 2022,
    month = may,
    booktitle = neurips,
    note = {Submitted} 
    }
    


  8. K. D. Smith, F. Seccamonte, A. Swami, and F. Bullo. Physics-Informed Implicit Representations of Network Flows. In Advances in Neural Information Processing Systems, May 2022. Note: Submitted.
    @InProceedings{ kds-fs-as-fb:21n,
    author = {K. D. Smith and F. Seccamonte and A. Swami and F. Bullo},
    title = {Physics-Informed Implicit Representations of Network Flows},
    year = 2022,
    month = may,
    booktitle = neurips,
    note = {Submitted} 
    }
    


Miscellaneous
  1. K. D. Smith. High-Order Tomography, 2022.
    @Misc{ kds:22,
    author = {K. D. Smith},
    title = {High-Order Tomography},
    year = 2022 
    }
    



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