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An introduction to the theory of spin glasses
Altieri, A., & Baity-Jesi, M. (2024). An introduction to the theory of spin glasses. In T. Chakraborty (Ed.), Reference module in materials science and materials engineering. Encyclopedia of condensed matter physics (pp. 361-370). https://doi.org/10.1016/B978-0-323-90800-9.00249-3
Multifractality in spin glasses
Baity-Jesi, M., Calore, E., Cruz, A., Fernández, L. A., Gil-Narvión, J. M., Pemartín, I. G. A., … Yllanes, D. (2024). Multifractality in spin glasses. Proceedings of the National Academy of Sciences of the United States of America PNAS, 121(2), e2312880120 (7 pp.). https://doi.org/10.1073/pnas.2312880120
Memory and rejuvenation effects in spin glasses are governed by more than one length scale
Baity-Jesi, M., Calore, E., Cruz, A., Fernandez, L. A., Gil-Narvion, J. M., Gonzalez-Adalid Pemartin, I., … Yllanes, D. (2023). Memory and rejuvenation effects in spin glasses are governed by more than one length scale. Nature Physics, 19(7), 978-985. https://doi.org/10.1038/s41567-023-02014-6
A theoretical analysis of the learning dynamics under class imbalance
Francazi, E., Baity-Jesi, M., & Lucchi, A. (2023). A theoretical analysis of the learning dynamics under class imbalance. In A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato, & J. Scarlett (Eds.), Proceedings of machine learning research: Vol. 202. Proceedings of the 40th international conference on machine learning (pp. 10285-10322). PMLR.
Linking human impacts to community processes in terrestrial and freshwater ecosystems
McFadden, I. R., Sendek, A., Brosse, M., Bach, P. M., Baity‐Jesi, M., Bolliger, J., … Narwani, A. (2023). Linking human impacts to community processes in terrestrial and freshwater ecosystems. Ecology Letters, 26(2), 203-218. https://doi.org/10.1111/ele.14153
Modeling node exposure for community detection in networks
Othman, S., Schulz, J., Baity-Jesi, M., & De Bacco, C. (2023). Modeling node exposure for community detection in networks. In H. Cherifi, R. N. Mantegna, L. M. Rocha, C. Cherifi, & S. Micciche (Eds.), Studies in computational intelligence: Vol. 1078. Complex networks and their applications XI. Proceedings of the eleventh international conference on complex networks and their applications: complex networks 2022 - volume 2 (pp. 233-244). https://doi.org/10.1007/978-3-031-21131-7_18
Superposition principle and nonlinear response in spin glasses
Paga, I., Zhai, Q., Baity-Jesi, M., Calore, E., Cruz, A., Cummings, C., … Yllanes, D. (2023). Superposition principle and nonlinear response in spin glasses. Physical Review B, 107(21), 214436 (21 pp.). https://doi.org/10.1103/PhysRevB.107.214436
A benchmark dataset for machine learning in ecotoxicology
Schür, C., Gasser, L., Perez-Cruz, F., Schirmer, K., & Baity-Jesi, M. (2023). A benchmark dataset for machine learning in ecotoxicology. Scientific Data, 10(1), 718 (20 pp.). https://doi.org/10.1038/s41597-023-02612-2
Differentiable modelling to unify machine learning and physical models for geosciences
Shen, C., Appling, A. P., Gentine, P., Bandai, T., Gupta, H., Tartakovsky, A., … Lawson, K. (2023). Differentiable modelling to unify machine learning and physical models for geosciences. Nature Reviews Earth & Environment, 4, 552-567. https://doi.org/10.1038/s43017-023-00450-9
Competition between energy- and entropy-driven activation in glasses
Carbone, M. R., & Baity-Jesi, M. (2022). Competition between energy- and entropy-driven activation in glasses. Physical Review E, 106(2), 024603 (7 pp.). https://doi.org/10.1103/PhysRevE.106.024603
Improving hydrologic models for predictions and process understanding using neural ODEs
Höge, M., Scheidegger, A., Baity-Jesi, M., Albert, C., & Fenicia, F. (2022). Improving hydrologic models for predictions and process understanding using neural ODEs. Hydrology and Earth System Sciences, 26(19), 5085-5102. https://doi.org/10.5194/hess-26-5085-2022
Ensembles of data-efficient vision transformers as a new paradigm for automated classification in ecology
Kyathanahally, S. P., Hardeman, T., Reyes, M., Merz, E., Bulas, T., Brun, P., … Baity-Jesi, M. (2022). Ensembles of data-efficient vision transformers as a new paradigm for automated classification in ecology. Scientific Reports, 12, 18590 (11 pp.). https://doi.org/10.1038/s41598-022-21910-0
Predicting chemical hazard across taxa through machine learning
Wu, J., D'Ambrosi, S., Ammann, L., Stadnicka-Michalak, J., Schirmer, K., & Baity-Jesi, M. (2022). Predicting chemical hazard across taxa through machine learning. Environment International, 163, 107184 (15 pp.). https://doi.org/10.1016/j.envint.2022.107184
Revisiting the concept of activation in supercooled liquids
Baity-Jesi, M., Biroli, G., & Reichman, D. R. (2021). Revisiting the concept of activation in supercooled liquids. European Physical Journal E: Soft Matter and Biological Physics, 44(6), 77 (10 pp.). https://doi.org/10.1140/epje/s10189-021-00077-y
Temperature chaos is present in off-equilibrium spin-glass dynamics
Baity-Jesi, M., Calore, E., Cruz, A., Fernandez, L. A., Gil-Narvion, J. M., Gonzalez-Adalid Pemartin, I., … Yllanes, D. (2021). Temperature chaos is present in off-equilibrium spin-glass dynamics. Communications Physics, 4(1), 74 (7 pp.). https://doi.org/10.1038/s42005-021-00565-9
Deep learning classification of Lake Zooplankton
Kyathanahally, S. P., Hardeman, T., Merz, E., Bulas, T., Reyes, M., Isles, P., … Baity-Jesi, M. (2021). Deep learning classification of Lake Zooplankton. Frontiers in Microbiology, 12, 746297 (13 pp.). https://doi.org/10.3389/fmicb.2021.746297
Underwater dual-magnification imaging for automated lake plankton monitoring
Merz, E., Kozakiewicz, T., Reyes, M., Ebi, C., Isles, P., Baity-Jesi, M., … Pomati, F. (2021). Underwater dual-magnification imaging for automated lake plankton monitoring. Water Research, 203, 117524 (12 pp.). https://doi.org/10.1016/j.watres.2021.117524
Spin-glass dynamics in the presence of a magnetic field: Exploration of microscopic properties
Paga, I., Zhai, Q., Baity-Jesi, M., Calore, E., Cruz, A., Fernandez, L. A., … Yllanes, D. (2021). Spin-glass dynamics in the presence of a magnetic field: Exploration of microscopic properties. Journal of Statistical Mechanics, 2021(3), 033301 (49 pp.). https://doi.org/10.1088/1742-5468/abdfca
Effective traplike activated dynamics in a continuous landscape
Carbone, M. R., Astuti, V., & Baity-Jesi, M. (2020). Effective traplike activated dynamics in a continuous landscape. Physical Review E, 101(5), 052304 (11 pp.). https://doi.org/10.1103/PhysRevE.101.052304
Scaling law describes the spin-glass response in theory, experiments, and simulations
Zhai, Q., Paga, I., Baity-Jesi, M., Calore, E., Cruz, A., Fernandez, L. A., … Yllanes, D. (2020). Scaling law describes the spin-glass response in theory, experiments, and simulations. Physical Review Letters, 125(23), 237202 (6 pp.). https://doi.org/10.1103/PhysRevLett.125.237202