Carlo Lucibello

711 total citations
29 papers, 353 citations indexed

About

Carlo Lucibello is a scholar working on Artificial Intelligence, Condensed Matter Physics and Statistical and Nonlinear Physics. According to data from OpenAlex, Carlo Lucibello has authored 29 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Condensed Matter Physics and 6 papers in Statistical and Nonlinear Physics. Recurrent topics in Carlo Lucibello's work include Neural Networks and Applications (9 papers), Theoretical and Computational Physics (6 papers) and Neural dynamics and brain function (4 papers). Carlo Lucibello is often cited by papers focused on Neural Networks and Applications (9 papers), Theoretical and Computational Physics (6 papers) and Neural dynamics and brain function (4 papers). Carlo Lucibello collaborates with scholars based in Italy, United States and Switzerland. Carlo Lucibello's co-authors include Riccardo Zecchina, Carlo Baldassi, Luca Saglietti, Alessandro Ingrosso, Giorgio Parisi, Gabriele Sicuro, Christian Borgs, Jennifer Chayes, Tommaso Rizzo and Marc Mézard and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and PLoS ONE.

In The Last Decade

Carlo Lucibello

24 papers receiving 342 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Carlo Lucibello Italy 12 175 76 71 53 46 29 353
Sébastien Racanière United States 11 154 0.9× 69 0.9× 90 1.3× 48 0.9× 14 0.3× 23 427
Luca Saglietti Italy 7 157 0.9× 36 0.5× 23 0.3× 18 0.3× 36 0.8× 16 228
Alessandro Ingrosso Italy 8 160 0.9× 58 0.8× 20 0.3× 19 0.4× 136 3.0× 14 341
Giuseppe Genovese Switzerland 10 106 0.6× 111 1.5× 101 1.4× 51 1.0× 37 0.8× 21 269
Timothy L. H. Watkin United Kingdom 8 409 2.3× 156 2.1× 65 0.9× 26 0.5× 78 1.7× 12 484
D. Easwaramoorthy India 9 51 0.3× 88 1.2× 16 0.2× 11 0.2× 78 1.7× 30 364
Ronen Eldan Israel 10 136 0.8× 48 0.6× 26 0.4× 109 2.1× 4 0.1× 27 397
Léo Miolane France 6 78 0.4× 32 0.4× 19 0.3× 118 2.2× 8 0.2× 7 241
Albrecht Rau United Kingdom 7 362 2.1× 128 1.7× 51 0.7× 14 0.3× 69 1.5× 14 415
D.P. Playne New Zealand 11 39 0.2× 69 0.9× 60 0.8× 9 0.2× 8 0.2× 37 372

Countries citing papers authored by Carlo Lucibello

Since Specialization
Citations

This map shows the geographic impact of Carlo Lucibello's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Carlo Lucibello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlo Lucibello more than expected).

Fields of papers citing papers by Carlo Lucibello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carlo Lucibello. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Carlo Lucibello. The network helps show where Carlo Lucibello may publish in the future.

Co-authorship network of co-authors of Carlo Lucibello

This figure shows the co-authorship network connecting the top 25 collaborators of Carlo Lucibello. A scholar is included among the top collaborators of Carlo Lucibello based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Carlo Lucibello. Carlo Lucibello is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lucibello, Carlo, et al.. (2025). Random features Hopfield networks generalize retrieval to previously unseen examples. Physica A Statistical Mechanics and its Applications. 678. 130946–130946.
2.
Lucibello, Carlo, et al.. (2025). Phase diagram of compressed sensing with ℓ 0 -norm regularization. Journal of Statistical Mechanics Theory and Experiment. 2025(6). 63402–63402.
3.
Ambrogioni, Luca, et al.. (2025). Memorization and generalization in generative diffusion under the manifold hypothesis. Journal of Statistical Mechanics Theory and Experiment. 2025(7). 73401–73401.
4.
Lucibello, Carlo & Marc Mézard. (2024). Exponential Capacity of Dense Associative Memories. Physical Review Letters. 132(7). 77301–77301. 19 indexed citations
5.
Ibáñez-Berganza, Miguel, Carlo Lucibello, Luca Mariani, & Giovanni Pezzulo. (2024). Information-theoretical analysis of the neural code for decoupled face representation. PLoS ONE. 19(1). e0295054–e0295054. 1 indexed citations
6.
Lucibello, Carlo, et al.. (2023). Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 323–328. 1 indexed citations
7.
Lucibello, Carlo, et al.. (2023). Storage and Learning Phase Transitions in the Random-Features Hopfield Model. Physical Review Letters. 131(25). 257301–257301. 6 indexed citations
8.
Ibáñez-Berganza, Miguel, et al.. (2023). Noise cleaning the precision matrix of short time series. Physical review. E. 108(2). 24313–24313. 3 indexed citations
9.
Lucibello, Carlo, et al.. (2023). Star-Shaped Space of Solutions of the Spherical Negative Perceptron. Physical Review Letters. 131(22). 227301–227301. 6 indexed citations
10.
Lucibello, Carlo, et al.. (2022). Unexpected Upper Critical Dimension for Spin Glass Models in a Field Predicted by the Loop Expansion around the Bethe Solution at Zero Temperature. Physical Review Letters. 128(7). 75702–75702. 11 indexed citations
11.
Feinauer, Christoph, et al.. (2022). Interpretable pairwise distillations for generative protein sequence models. PLoS Computational Biology. 18(6). e1010219–e1010219. 2 indexed citations
12.
Lucibello, Carlo, et al.. (2021). Entropic gradient descent algorithms and wide flat minima. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 15 indexed citations
13.
Lucibello, Carlo, et al.. (2020). Loop expansion around the Bethe solution for the random magnetic field Ising ferromagnets at zero temperature. Proceedings of the National Academy of Sciences. 117(5). 2268–2274. 11 indexed citations
14.
Saglietti, Luca, Yue M. Lu, & Carlo Lucibello. (2020). Generalized approximate survey propagation for high-dimensional estimation *. Journal of Statistical Mechanics Theory and Experiment. 2020(12). 124003–124003.
15.
Saglietti, Luca, Yue M. Lu, & Carlo Lucibello. (2019). Generalized Approximate Survey Propagation for High-Dimensional Estimation. arXiv (Cornell University). 4173–4182. 2 indexed citations
16.
Baldassi, Carlo, Hilbert J. Kappen, Carlo Lucibello, et al.. (2018). Role of Synaptic Stochasticity in Training Low-Precision Neural Networks. Physical Review Letters. 120(26). 268103–268103. 12 indexed citations
17.
Baldassi, Carlo, Christian Borgs, Jennifer Chayes, et al.. (2016). Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes. Proceedings of the National Academy of Sciences. 113(48). E7655–E7662. 76 indexed citations
18.
Baldassi, Carlo, et al.. (2016). Learning may need only a few bits of synaptic precision. Physical review. E. 93(5). 52313–52313. 13 indexed citations
19.
Baldassi, Carlo, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, & Riccardo Zecchina. (2015). Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses. Physical Review Letters. 115(12). 128101–128101. 61 indexed citations
20.
Lucibello, Carlo, Flaviano Morone, Giorgio Parisi, Federico Ricci‐Tersenghi, & Tommaso Rizzo. (2014). Finite-size corrections to disordered Ising models on random regular graphs. Physical Review E. 90(1). 12146–12146. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026