Diego Garlaschelli
Hoogleraar Theoretische natuurkunde
- Naam
- Prof.dr. D. Garlaschelli
- Telefoon
- +31 71 527 5510
- garlaschelli@lorentz.leidenuniv.nl
- ORCID iD
- 0000-0001-6035-1783
Meer informatie over Diego Garlaschelli
Promovendi
Nieuws
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Nieuwe hoogleraar Theoretische Natuurkunde: 'De problemen die ik bestudeer kunnen overal uit de maatschappij komen' -
Algemeen kader voor systeemanalyse in Natuurkunde en Economie -
Leids financieel model winnaar in test centrale banken -
Studium Generale-reeks over complexe netwerken afgetrapt -
Bewijs gevonden tegen eeuw oude natuurkundige aanname -
Complexiteitstheorie moet nieuwe financiële crashes voorkomen -
Wat hebben oerknal en economie gemeen? -
De paradox van het delen -
Aankondiging College Econophysics
Hoogleraar Theoretische natuurkunde
- Wiskunde en Natuurwetenschappen
- Leiden Instituut Onderzoek Natuurkunde
- LION - Theoretical Physics
- Di Vece M., Pijpers F.P. & Garlaschelli D. (2024), Commodity-specific triads in the Dutch inter-industry production network, Scientific Reports 14: 3625.
- Gallo A., Garlaschelli D., Lambiotte R., Saracco F. & Squartini T. (2024), Testing structural balance theories in heterogeneous signed networks, Communications Physics 7: 154.
- Gallo A., Garlaschelli D., Lambiotte R., Saracco F. & Squartini. T. (2024), Addendum: testing structural balance theories in heterogeneous signed networks, Communications Physics 7: 312.
- Clemente Giulio Virginio Garlaschelli Diego (2024), Linking through time: Memory-enhanced community discovery in temporal networks, Physical Review Research 6: 043204.
- Neal Zachary P. Cadieux Annabell Garlaschelli Diego Gotelli Nicholas J. Saracco Fabio Squartini Tiziano Shutters Shade T. Ulrich Werner Wang Guanyang Strona Giovanni (2024), Pattern detection in bipartite networks: A review of terminology, applications, and methods, PLOS Complex Systems 1: e0000010.
- Zema Sebastiano Michele Fagiolo Giorgio Squartini Tiziano Garlaschelli Diego (2024), Mesoscopic structure of the stock market and portfolio optimization, Journal of economic interaction and coordination (Garlaschelli) : .
- Gabrielli A., Macchiati V. & Garlaschelli D. (2024), Critical density for network reconstruction. In: Cantone D. & Pulvirenti A. (red.), From Computational Logic to Computational Biology. Lecture Notes in Computer Science nr. 14070. Cham: Springer. 223–249.
- Macchiati V., Mazzarisi P. & Garlaschelli. D. (2024), Interbank network reconstruction enforcing density and reciprocity, Chaos, Solitons and Fractals 186(115279): 1-16 (120883).
- Mungo L., Brintrup A., Garlaschelli D. & Lafond F. (2024), Reconstructing supply network, Journal of Physics: Complexity 5(1): 012001.
- Somazzi A., Ferragina P. & Garlaschelli D. (2024), On nonlinear compression costs: when Shannon Meets Rényi, IEEE Access 12: 77750-77783.
- Di Vece M., Garlaschelli D. & Squartini T. (2023), Deterministic, quenched, and annealed parameter estimation for heterogeneous network models, Physical Review E 108(5): 054301.
- Zhang Q. & Garlaschelli D. (2023), Ensemble nonequivalence and Bose-Einstein condensation in weighted networks, Chaos, Solitons and Fractals 172: 113546.
- Bayrakdar N., Gemmetto V. & Garlaschelli D. (2023), Local phase transitions in a model of multiplex networks with heterogeneous degrees and inter-layer coupling, Entropy 25(5): 828.
- Garuccio E., Lalli M. & Garlaschelli D. (2023), Multiscale network renormalization: scale-invariance without geometry, Physical Review Research 5(4): 043101.
- Di Vece M., Garlaschelli D & Squartini T. (2023), Reconciling econometrics with continuous maximum-entropy network models, Chaos, Solitons and Fractals 166: 112958.
- Dionigi P., Garlaschelli D., Hollander W.T.F. den, Hazra R.S. & Mandjes M. (2023), Central limit theorem for the principal eigenvalue and eigenvector of Chung-Lu random graphs, Journal of Physics: Complexity 4(1): 015008.
- Di Vece M., Garlaschelli D. & Squartini T. (2022), Gravity models of networks: integrating maximum-entropy and econometric approaches, Physical Review Research 4(3): 033105.
- Mircea M., Hochane M., Fan X., Chuva de Sousa Lopes S.M., Garlaschelli D. & Semrau S. (2022), Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations, Genome Biology 23(1): 18.
- Caruso T., Clemente G.V., Rillig M.C. & Garlaschelli D. (2022), Fluctuating ecological networks: a synthesis of maximum‐entropy approaches for pattern detection and process inference, Methods in Ecology and Evolution 13(11): 2306-2317.
- Ialongo L.N., Valc C. de, Marchese E., Jansen F., Zmarrou H., Squartini T. & Garlaschelli D. (2022), Reconstructing firm-level interactions in the Dutch input-output network from production constraints, Scientific Reports 12(1): 11847.
- Zhang Q. & Garlaschelli D. (2022), Strong ensemble nonequivalence in systems with local constraints, New Journal of Physics 24(4): 043011.
- Kralingen M. van, Garlaschelli D., Scholtus K. & Lelyveld I. van (2021), Crowded trades, market clustering, and price instability, Entropy 23(3): 336.
- Anagnostou I., Squartini T., Kandhai D. & Garlaschelli D. (2021), Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling, Quantitative Finance 21(9): 1501-1518.
- Bardoscia M., Barucca P., Battiston S., Caccioli F., Cimini G., Garlaschelli D., Saracco F., Squartini T. & Caldarelli G. (2021), The physics of financial networks, Nature Reviews Physics 3: 490-507.
- De Castro F., Adl S.M., Allesina S., Bardgett R.D., Bolger T., Dalzell J.J., Emmerson M., Fleming T., Garlaschelli D., Grilli J., Hannula S.E., De Vries F., Lindo Z., Maule A.G., Opik M., Rillig M.C., Veresoglou S.D., Wall D.H. & Caruso T. (2021), Local stability properties of complex, species‐rich soil food webs with functional block structure, Ecology and Evolution 11(22): 16070-16081.
- Dionigi P., Garlaschelli D., Hollander W.T.F. den & Mandjes M. (2021), A spectral signature of breaking of ensemble equivalence for constrained random graphs, Electronic Communications in Probability 26: 1-15.
- Bruno M., Saracco F., Garlaschelli D., Tessone C.J. & Caldarelli G. (2020), The ambiguity of nestedness under soft and hard constraints, Scientific Reports 10: 19903.
- Parisi F., Squartini T. & Garlaschelli D. (2020), A faster horse on a safer trail: generalized inference for the efficient reconstruction of weighted networks, New Journal of Physics 22: 053053.
- Garlaschelli D., Hollander W.T.F. den, Meylahn J.M. & Zeegers B.P. (2019), Synchronization of phase oscillators on the hierarchical lattice, Journal of Statistical Physics 174(1): 188-218.
- Almog A., Bird R. & Garlaschelli D. (2019), Enhanced gravity model of trade: Reconciling macroeconomic and network models, Frontiers in Physics 7: 55.
- Almog A., Buijink M.R., Roethler O., Michel S., Meijer J.H., Rohling J.H.T. & Garlaschelli D. (2019), Uncovering functional signature in neural systems via random matrix theory, PLoS Computational Biology 15(5): e1006934.
- Cimini G., Squartini T., Saracco F., Garlaschelli D., Gabrielli A. & Caldarelli G. (2019), The statistical physics of real-world networks, Nature Reviews Physics 1: 58-71.
- Babeanu A.I., Vis J.M. van de & Garlaschelli D. (2018), Ultrametricity increases the predictability of cultural dynamics, New Journal of Physics 20: 103026.
- Babeanu A.I. & Garlaschelli D. (2018), Evidence for Mixed Rationalities in Preference Formation, Complexity 2018: 3615476.
- Squartini T., Gabrielli A., Garlaschelli D., Gili T., Bifone A. & Caccioli F. (2018), Complexity in neural and financial systems: From time-series to networks, Complexity 2018: 3132940.
- Squartini T., Caldarelli G., Cimini G., Gabrielli A. & Garlaschelli D. (2018), Reconstruction methods for networks: The case of economic and financial systems, Physics Reports 757: 1-47.
- Garlaschelli D., Hollander W.T.F. den & Roccaverde A. (2018), Covariance Structure Behind Breaking of Ensemble Equivalence in Random Graphs, Journal of Statistical Physics 173(3-4): 644-662.
- Garlaschelli D., Hofstad R. van der, Hollander F. den & Mandjes M. (2018), Special Issue of Journal of Statistical Physics Devoted to Complex Networks, Journal of Statistical Physics 173(3-4): 439-447.
- Krantz R., Gemmetto V. & Garlaschelli D. (2018), Maximum-entropy tools for economic fitness and complexity, Entropy 20(10): 743.
- Maulana A., Gametto V., Garlaschelli D., Yevesyeva I. & Emmerich M.T.M. (2017), Modularities Maximization in Multiplex network Analysis Using Many-Objective Optimization. IEEE SSCI 2016 6 december 2016 - 9 december 2016 nr. 2016 IEEE Symposium Series on Computational Intelligence (SSCI): IEEE. 1-8.
- Almog A., Squartini T. & Garlaschelli D. (2017), The double role of GDP in shaping the structure of the international trade network, International Journal of Computational Economics and Econometrics 7(4): 381-398.
- Babeanu A.I., Talman L. & Garlaschelli D. (2017), Signs of universality in the structure of culture, The European Physical Journal B 90: 237.
- Squartini T. & Garlaschelli D. (2017), Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics. Briefs in Complexity. Cham: Springer International Publishing.
- Garlaschelli D., Hollander W.T.F. den & Roccaverde A. (2017), Ensemble nonequivalence in random graphs with modular structure, Journal of Physics A: Mathematical and Theoretical 50: 015001.
- Squartini T., Almog A., Caldarelli G., Lelyveld I. van, Garlaschelli D. & Cimini G. (2017), Enhanced capital-asset pricing model for the reconstruction of bipartite financial networks, Physical Review E 96: 032315.
- Battiston S., Farmer D., Flache A., Garlaschell D., Haldane A., Heesterbeek H., Hommes C., Jaeger C., May R. & Scheffer M. (2016), Financial complexity: Accounting for fraud-Response, Science 352(6283): 302-302.
- Buijink M.R., Almog A., Wit C.B., Roethler O., Olde Engberink A.H.O., Meijer J.H., Garlaschelli D., Rohling J.H.T. & Michel S. (2016), Evidence for Weakened Intercellular Coupling in the Mammalian Circadian Clock under Long Photoperiod, PLoS ONE 11(12): e0168954.
- Valori L., Giannuzzi G.L., Facchini A., Squartini T., Garlaschelli D. & Basosi R. (2016), A generation-attraction model for renewable energy flows in Italy: A complex network approach, European Physical Journal - Special Topics 225(10): 1913-1927.
- Battiston S., Farmer J.D., Flache A., Garlaschelli D., Haldane A.G., Heesterbeek H., Hommes C., Jaeger C., May R. & Scheffer M. (2016), Complexity theory and financial regulation, Science 351(6275): 818-819.
- Maulana A., Gemmetto V., Garlaschelli D. & Emmerich M.T.M. (2016), Computing Pareto Fronts of Modularities in Multiplex Economic Network Analysis, 2016 IEEE Symposium Series on Computational Intelligence (SSCI). CENTERIS 2016 : International Conference on ENTERprise Information Systems 5 oktober 2016 - 8 oktober 2016: IEEE Xplore. 1-8.
- Palchykov V., Gemmetto V., Boiarsky O. & Garlaschelli D. (2016), Ground truth? Concept-based communities versus the external classification of physics manuscripts, EPJ Data Science 5: 28.
- Gemmetto V., Squartini T., Picciolo F., Ruzzenenti F. & Garlaschelli D. (2016), Multiplexity and multireciprocity in directed multiplexes, Physical Review E 94(4): 042316.
- Garlaschelli D., Hollander W.T.F. & Roccaverde A. (2016), Ensemble nonequivalence in random graphs with modular structure, Journal of Physics A: Mathematical and Theoretical 50(1): 015001.
- Squartini T., Mastrandrea R. & Garlaschelli D. (2015), Unbiased sampling of network ensembles, New Journal of Physics 17: 023052.
- Almog A., Besamusca F., MacMahon M. & Garlaschelli D. (2015), Mesoscopic community structure of financial markets revealed by price and sign fluctuations, PLoS ONE 10: e0133679.
- Almog A., Squartini T. & Garlaschelli D. (2015), A GDP-driven model for the binary and weighted structure of the International Trade Network, New Journal of Physics 17: 013009.
- Cimini G., Squartini T., Gabrielli A. & Garlaschelli D. (2015), Estimating topological properties of weighted networks from limited information, Physical Review E 92(4): 040802.
- Cimini G., Squartini T., Garlaschelli D. & Gabrielli A. (2015), Systemic risk analysis on reconstructed economic and financial networks, Scientific Reports 5: 15758.
- Cimini G., Squartini T., Musmeci N., Puliga M., Gabrielli A., Garlaschelli D., Battiston S. & Caldarelli G. (2015), Reconstructing topological properties of complex networks using the fitness model, 8852(323-333): .
- Gemmetto V. & Garlaschelli D. (2015), Multiplexity versus correlation: The role of local constraints in real multiplexes, Scientific Reports 5: 9120.
- Squartini T., Ser-Giacomi E., Garlaschelli D. & Judge G. (2015), Information recovery in behavioral networks, PLoS ONE 10(5): e0125077.
- Squartini T., Mol J. de, Hollander W.T.F. den & Garlaschelli D. (2015), Breaking of ensemble equivalence in networks, Physical Review Letters 115(26): 268701.
- Squartini T. & Garlaschelli D. (2015), Stationarity, non-stationarity and early warning signals in economic networks, Journal of complex networks 3: 1-21.
- Garlaschelli D., Hollander W.T.F den & Roccaverde A. (2015), Complexe netwerken vanuit fysisch perspectief, Nieuw Archief voor Wiskunde 5/16(3): 207-209.
- MacMahon M. & Garlaschelli D. (2015), Community detection for correlation matrices, Physical Review X 5: 021006.
- Almog A. & Garlaschelli D. (2014), Binary versus non-binary information in real time series: Empirical results and maximum-entropy matrix models, New Journal of Physics 16: 093015.
- Mastrandrea R., Squartini T., Fagiolo G. & Garlaschelli D. (2014), Reconstructing the world trade multiplex: the role of intensive and extensive biases, Physical Review E 90(6): 062804.
- Mastrandrea R., Squartini T., Fagiolo G. & Garlaschelli D. (2014), Enhanced reconstruction of weighted networks from strengths and degrees, New Journal of Physics 16: 043022.
- Garlaschelli D., Ahnert S.E., Fink T.M.A. & Caldarelli G. (2013), Low-temperature behaviour of social and economic networks, Entropy 15: 3148-3169.
- Garlaschelli D., Ahnert S.E., Fink T.M.A. & Caldarelli G. (2013), Optimal scales in weighted networks, 8238: 346-359.
- Squartini T., Picciolo F., Ruzzenenti F. & Garlaschelli D. (2013), Reciprocity of weighted networks, Scientific Reports 3: 2729.
- Bottini S., Bernini A., Chiara M. de, Garlaschelli D., Spiga O., Dioguardi M., Vannuccini E., Tramontano A. & Niccolai N. (2013), ProCoCoA: A quantitative approach for analyzing protein core composition, Computational biology and chemistry 43: 29-34.
- Squartini T., Lelyveld I. van & Garlaschelli D. (2013), Early-warning signals of topological collapse in interbank networks, Scientific Reports 3: 3357.
- Zlatic V., Garlaschelli D. & Caldarelli G. (2012), Networks with arbitrary edge multiplicities, Europhysics Letters 97: .
- Fagiolo G., Squartini T. & Garlaschelli D. (2012), Null models of economic networks: The case of the world trade web, Journal of economic interaction and coordination (Garlaschelli) September: .
- Ruzzenenti F., Picciolo F., Basosi R. & Garlaschelli D. (2012), Spatial effects in real networks: Measures, null models, and applications, Physical Review E 86(6): 066110.
- Valori L., Picciolo F., Allandottir A. & Garlaschelli D. (2012), Reconciling long-term cultural diversity and short-term collective social behavior, Proceedings of the National Academy of Sciences 109: 1068-1073.
- Squartini T. & Garlaschelli D. (2012), Triadic motifs and dyadic self-organization in the world trade network, 7166: 24-35.
- Garlaschelli D. & Denteneer P.J.H. (2011), Econophysics: inzicht in economische complexiteit, Nederlands Tijdschrift voor Natuurkunde 77(11): .
- Squartini T., Fagiolo G. & Garlaschelli D. (2011), Randomizing world trade. II. A weighted network analysis, Physical Review E 84(4): 046118.
- Squartini T., Fagiolo G. & Garlaschelli D. (2011), Randomizing world trade. I. A binary network analysis, Physical Review E 84(4): 046117.
- Associate Professor