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Item 2022 Klein Lecture Parental Education and Invention : The Finnish Enigma(Wiley-Blackwell, 2023-05) Aghion, Philippe; Akcigit, Ufuk; Hyytinen, Ari; Toivanen, Otto; The London School of Economics and Political Science; University of Chicago; Hanken School of Economics; Department of Economics; Department of EconomicsWhy is invention strongly positively correlated with parental income not only in the United States but also in Finland, which displays low income inequality and high social mobility? Using data on 1.45 M Finnish individuals and their parents, we find the following: (i) the positive association between parental income and off-spring probability of inventing is greatly reduced when controlling for parental education; (ii) instrumenting for the parents having an MSc degree using distance to nearest university reveals a large causal effect of parental education on offspring probability of inventing; and (iii) the causal effect of parental education has been markedly weakened by the introduction in the early 1970s of a comprehensive schooling reform.Item Breaking quadratic time for small vertex connectivity and an approximation scheme(2019-06-23) Nanongkai, Danupon; Saranurak, Thatchaphol; Yingchareonthawornchai, Sorrachai; KTH Royal Institute of Technology; University of Chicago; Department of Computer Science; Charikar, Moses; Cohen, EdithVertex connectivity a classic extensively-studied problem. Given an integer k, its goal is to decide if an n-node m-edge graph can be disconnected by removing k vertices. Although a linear-time algorithm was postulated since 1974 [Aho, Hopcroft and Ullman], and despite its sibling problem of edge connectivity being resolved over two decades ago [Karger STOC’96], so far no vertex connectivity algorithms are faster than O(n2) time even for k = 4 and m = O(n). In the simplest case where m = O(n) and k = O(1), the O(n2) bound dates five decades back to [Kleitman IEEE Trans. Circuit Theory’69]. For higher m, O(m) time is known for k ≤ 3 [Tarjan FOCS’71; Hopcroft, Tarjan SICOMP’73], the first O(n2) time is from [Kanevsky, Ramachandran, FOCS’87] for k = 4 and from [Nagamochi, Ibaraki, Algorithmica’92] for k = O(1). For general k and m, the best bound is Õ (min(kn2, nω + nkω )) [Henzinger, Rao, Gabow FOCS’96; Linial, Lovász, Wigderson FOCS’86] where Õ hides polylogarithmic terms and ω < 2.38 is the matrix multiplication exponent. In this paper, we present a randomized Monte Carlo algorithm with Õ (m + k7/3n4/3) time for any k = O(n). This gives the first subquadratic time bound for any 4 ≤ k ≤ o(n2/7) (subquadratic time refers to O(m) + o(n2) time.) and improves all above classic bounds for all k ≤ n0.44. We also present a new randomized Monte Carlo (1 + ϵ)-approximation algorithm that is strictly faster than the previous Henzinger’s 2-approximation algorithm [J. Algorithms’97] and all previous exact algorithms. The story is the same for the directed case, where our exact Õ (min(km2/3n, km4/3))-time for any k = O(n) and (1 + ϵ)-approximation algorithms improve all previous exact bounds. Additionally, our algorithm is the first approximation algorithm on directed graphs. The key to our results is to avoid computing single-source connectivity, which was needed by all previous exact algorithms and is not known to admit o(n2) time. Instead, we design the first local algorithm for computing vertex connectivity; without reading the whole graph, our algorithm can find a separator of size at most k or certify that there is no separator of size at most k “near” a given seed node.Item Can CMB surveys help the AGN community?(2017-08-30) Partridge, Bruce; Bonavera, Laura; López-Caniego, Marcos; Datta, Rahul; Gonzalez-Nuevo, Joaquin; Gralla, Megan; Herranz, Diego; Lähteenmäki, Anne; Mocanu, Laura; Prince, Heather; Vieira, Joaquin; Whitehorn, Nathan; Zhang, Lizhong; Haverford College; University of Oviedo; European Space Astronomy Centre; NASA Goddard Space Flight Center; University of Arizona; Universidad de Cantabria; Metsähovi Radio Observatory; University of Chicago; Princeton University; University of Illinois at Urbana-Champaign; University of California Los Angeles; Department of Electronics and NanoengineeringContemporary projects to measure anisotropies in the cosmic microwave background (CMB) are now detecting hundreds to thousands of extragalactic radio sources, most of them blazars. As a member of a group of CMB scientists involved in the construction of catalogues of such sources and their analysis, I wish to point out the potential value of CMB surveys to studies of AGN jets and their polarization. Current CMB projects, for instance, reach mJy sensitivity, offer wide sky coverage, are "blind" and generally of uniform sensitivity across the sky (hence useful statistically), make essentially simultaneous multi-frequency observations at frequencies from 30 to 857 GHz, routinely offer repeated observations of sources with interesting cadences and now generally provide polarization measurements. The aim here is not to analyze in any depth the AGN science already derived from such projects, but rather to heighten awareness of their promise for the AGN community.Item Fast Methods for Posterior Inference of Two-Group Normal-Normal Models(International Society for Bayesian Analysis, 2023-09) Greengard, Philip; Hoskins, Jeremy; Margossian, Charles C.; Gabry, Jonah; Gelman, Andrew; Vehtari, Aki; Columbia University; University of Chicago; Computer Science Professors; Department of Computer ScienceWe describe a class of algorithms for evaluating posterior moments of certain Bayesian linear regression models with a normal likelihood and a normal prior on the regression coefficients. The proposed methods can be used for hierarchical mixed effects models with partial pooling over one group of predictors, as well as random effects models with partial pooling over two groups of predictors. We demonstrate the performance of the methods on two applications, one involving U.S. opinion polls and one involving the modeling of COVID-19 outbreaks in Israel using survey data. The algorithms involve analytical marginalization of regression coefficients followed by numerical integration of the remaining low-dimensional density. The dominant cost of the algorithms is an eigendecomposition computed once for each value of the outside parameter of integration. Our approach drastically reduces run times compared to state-of-the-art Markov chain Monte Carlo (MCMC) algorithms. The latter, in addition to being computationally expensive, can also be difficult to tune when applied to hierarchical models.Item Measuring, Quantifying, and Predicting the Cost-Accuracy Tradeoff(2019-12-01) Baughman, Matt; Chakubaji, Nifesh; Truong, Linh; Kreics, Krists; Chard, Kyle; Foster, Ian; University of Chicago; Department of Computer Science; Aalto University; Argonne National LaboratoryExponentially increasing data volumes, coupled with new modes of analysis have created significant new opportunities for data scientists. However, the stochastic nature of many data science techniques results in tradeoffs between costs and accuracy. For example, machine learning algorithms can be trained iteratively and indefinitely with diminishing returns in terms of accuracy. In this paper we explore the cost-accuracy tradeoff through three representative examples: we vary the number of models in an ensemble, the number of epochs used to train a machine learning model, and the amount of data used to train a machine learning model. We highlight the feasibility and benefits of being able to measure, quantify, and predict cost accuracy tradeoffs by demonstrating the presence and usability of these tradeoffs in two different case studies.Item Nonlocal thermoelectricity in a hybrid superconducting graphene device(2021-06-16) Golubev, D. S.; Kirsanov, N. S.; Tan, Z. B.; Laitinen, A.; Galda, A.; Vinokur, V. M.; Haque, M.; Savin, A.; Lesovik, G. B.; Hakonen, P. J.; Centre of Excellence in Quantum Technology, QTF; Department of Applied Physics; University of Chicago; OtaNano; Terra Quantum AG; Lesovik, Gordey; Vinokur, Valeril; Perelshtein, MikhailThe Seebeck effect producing voltage difference from temperature gradient has a wide spectrum of applications. Recent theoretical studies show that the Cooper pair splitting and the elastic co-tunneling can give rise to the nonlocal Seebeck effect in hybrid normal metal-superconductor-normal metal systems. Here we propose a coherent transport description of this nonlocal effect and validate its experimental observation in a graphene-based Cooper pair splitter.Item Phase estimation algorithm for the multibeam optical metrology(Nature Publishing Group, 2020-12-01) Zemlyanov, V. V.; Kirsanov, N. S.; Perelshtein, M. R.; Lykov, D. I.; Misochko, O. V.; Lebedev, M. V.; Vinokur, V. M.; Lesovik, G. B.; Moscow Institute of Physics and Technology; Quantum Circuits and Correlations; Department of Applied Physics; University of ChicagoUnitary Fourier transform lies at the core of the multitudinous computational and metrological algorithms. Here we show experimentally how the unitary Fourier transform-based phase estimation protocol, used namely in quantum metrology, can be translated into the classical linear optical framework. The developed setup made of beam splitters, mirrors and phase shifters demonstrates how the classical coherence, similarly to the quantum coherence, poses a resource for obtaining information about the measurable physical quantities. Our study opens route to the reliable implementation of the small-scale unitary algorithms on path-encoded qudits, thus establishing an easily accessible platform for unitary computation.Item Planck 2015 results(2016-10-01) Ade, P. A R; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J. P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J. F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R. R.; Chiang, H. C.; Chluba, J.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P L; Combet, C.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; De Bernardis, P.; De Rosa, A.; De Zotti, G.; Delabrouille, J.; Désert, F. X.; Di Valentino, E.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Farhang, M.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Gerbino, M.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Giusarma, E.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hamann, J.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J. M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Lewis, A.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Maciás-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Marchini, A.; Maris, M.; Martin, P. G.; Martinelli, M.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mcgehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J. B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Millea, M.; Mitra, S.; Miville-Deschênes, M. A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J. L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rouillé D'orfeuil, B.; Rowan-Robinson, M.; Rubinõ-Martín, J. A.; Rusholme, B.; Said, N.; Salvatelli, V.; Salvati, L.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Serra, P.; Shellard, E. P S; Spencer, L. D.; Spinelli, M.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A. S.; Sygnet, J. F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Trombetti, T.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Väliviita, J.; Van Tent, F.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; White, M.; White, S. D M; Wilkinson, A.; Yvon, D.; Zacchei, A.; Zonca, A.; Cardiff University; CNRS/IN2P3; Service d'Astrophysique CEA; Kavli Institute for Cosmology Cambridge; University of Cambridge; International School for Advanced Studies; IRAP; Universite de Toulouse; Instituto de Física de Cantabria (CSIC-Universidad de Cantabria); Jet Propulsion Laboratory, California Institute of Technology; AstroParticule et Cosmologie; Università Degli Studi di Padova; Istituto Nazionale di Fisica Nucleare, Sezione di Padova, I-35131 Padova, Italy; University of Granada; University of Manchester; UMR7095; CNRS; University College London; INAF/IASF Milano; Università degli Studi di Milano; Nicolaus Copernicus Astronomical Center; California Institute of Technology; University of Toronto; University of California at Berkeley; Lawrence Berkeley National Laboratory; Universite Paris Sorbonne - Paris IV; Institut d 'Astrophysique de Paris; INAF/IASF Bologna; Università di Ferrara; INFN, Sezione di Bologna; University of Oxford; UMR 5141; LERMA - Laboratoire d'Etudes du Rayonnement et de la Matiere en Astrophysique et Atmospheres; Laboratoire AIM, Service d’Astrophysique, DSM\IRFU, CEA\Saclay; Institut d'Astrophysique Spatiale; Princeton University; University of KwaZulu-Natal; Johns Hopkins University; Niels Bohr Institute; Stanford University; Imperial College London; University of Southern California; Universidad de Cantabria; Università La Sapienza; INAF, Osservatorio Astronomico di Padova; UMR 7095; Ludwig Maximilian University of Munich; Max-Planck-Institut für Astrophysik; Institut Universitaire de France; European Space Agcy, European Space Agency, ESAC, Planck Sci Off; University of Oslo; Shahid Beheshti University; Osservatorio Astronomico di Trieste; University of Chicago; National Taiwan University; Stockholms universitet; NORDITA; University of Warsaw; Università Degli Studi di Trieste; Istituto Nazionale di Fisica Nucleare; CERN; University of Sydney; McGill University; Centro de Estudios de la Física del Cosmos de Aragón; Technical University of Denmark; Florida State University; University of Helsinki; European Southern Observatory Santiago; ALMA Santiago Central Offices; University of California; Université de Genève; African Institute for Mathematical Sciences; Helsinki Institute of Physics; Aix Marseille Universite; Department of Radio Science and Engineering; Metsähovi Radio Observatory; INFN, Sezione di Ferrara; Centro de Gestão e Estudos Estratégicos; RWTH Aachen University; University of Sussex; INFN, Sezione di Padova; University of California, Santa Barbara; INAF, Osservatorio Astronomico di Trieste; Universite Paris-Sud; INFN, Sezione di Roma 1; University of Heidelberg; Gran Sasso Science Institute; CEA Saclay, CEA, DSM Irfu SPP; Inter-University Centre for Astronomy and Astrophysics; CNRS Centre National de la Recherche Scientifique; University of Nottingham; National University of Ireland; University of Copenhagen; ASI Science Data Center; RAS - Pn Lebedev Physics Institute; Haverford College; INAF, Osservatorio Astronomico di Roma; Institute for Space Sciences; Université Pierre and Marie Curie; Radboud University Nijmegen; Universities Space Research Association; Instituto Astrofisico de Canarias; CSIC; Universidad de La Laguna; Università di Roma Tor Vergata; Department of Applied Physics; ROTA – Topological superfluids; University of British Columbia; Special Astrophysical Observatory, Russian Academy of Sciences; Kazan Federal University; Space Research Institute, Russian Academy of Sciences; ESTEC - European Space Research and Technology Centre; Università degli Studi e-Campus; Universidad de Oviedo; Trinity College Dublin; INAF, Osservatorio Astrofisico di Catania; University of Illinois at Urbana-ChampaignThis paper presents cosmological results based on full-mission Planck observations of temperature and polarization anisotropies of the cosmic microwave background (CMB) radiation. Our results are in very good agreement with the 2013 analysis of the Planck nominal-mission temperature data, but with increased precision. The temperature and polarization power spectra are consistent with the standard spatially-flat 6-parameter ΛCDM cosmology with a power-law spectrum of adiabatic scalar perturbations (denoted "base ΛCDM" in this paper). From the Planck temperature data combined with Planck lensing, for this cosmology we find a Hubble constant, H0 = (67.8 ± 0.9) km s-1Mpc-1, a matter density parameter Ωm = 0.308 ± 0.012, and a tilted scalar spectral index with ns = 0.968 ± 0.006, consistent with the 2013 analysis. Note that in this abstract we quote 68% confidence limits on measured parameters and 95% upper limits on other parameters. We present the first results of polarization measurements with the Low FrequencyInstrument at large angular scales. Combined with the Planck temperature and lensing data, these measurements give a reionization optical depth of τ = 0.066 ± 0.016, corresponding to a reionization redshift of \hbox{$z-{\rm re}=8.8{+1.7}-{-1.4}$}. These results are consistent with those from WMAP polarization measurements cleaned for dust emission using 353-GHz polarization maps from the High Frequency Instrument. We find no evidence for any departure from base ΛCDM in the neutrino sector of the theory; for example, combining Planck observations with other astrophysical data we find Neff = 3.15 ± 0.23 for the effective number of relativistic degrees of freedom, consistent with the value Neff = 3.046 of the Standard Model of particle physics. The sum of neutrino masses is constrained to â'mν < 0.23 eV. The spatial curvature of our Universe is found to be very close to zero, with | ΩK | < 0.005. Adding a tensor component as a single-parameter extension to base ΛCDM we find an upper limit on the tensor-to-scalar ratio of r0.002< 0.11, consistent with the Planck 2013 results and consistent with the B-mode polarization constraints from a joint analysis of BICEP2, Keck Array, and Planck (BKP) data. Adding the BKP B-mode data to our analysis leads to a tighter constraint of r0.002 < 0.09 and disfavours inflationarymodels with a V(φ) φ2 potential. The addition of Planck polarization data leads to strong constraints on deviations from a purely adiabatic spectrum of fluctuations. We find no evidence for any contribution from isocurvature perturbations or from cosmic defects. Combining Planck data with other astrophysical data, including Type Ia supernovae, the equation of state of dark energy is constrained to w =-1.006 ± 0.045, consistent with the expected value for a cosmological constant. The standard big bang nucleosynthesis predictions for the helium and deuterium abundances for the best-fit Planck base ΛCDM cosmology are in excellent agreement with observations. We also constraints on annihilating dark matter and onpossible deviations from the standard recombination history. In neither case do we find no evidence for new physics. The Planck results for base ΛCDM are in good agreement with baryon acoustic oscillation data and with the JLA sample of Type Ia supernovae. However, as in the 2013 analysis, the amplitude of the fluctuation spectrum is found to be higher than inferred from some analyses of rich cluster counts and weak gravitational lensing. We show that these tensions cannot easily be resolved with simple modifications of the base ΛCDM cosmology. Apart from these tensions, the base ΛCDM cosmology provides an excellent description of the Planck CMB observations and many other astrophysical data sets.Item Thermal and mechanical properties of the clathrate-II Na24Si136(American Physical Society, 2022-06-30) Beekman, Matt; Karttunen, Antti J.; Wong-Ng, Winnie; Zhang, Mingjian; Chen, Yu Sheng; Posadas, Christian; Jarymowycz, Andrew; Cruse, E.; Peng, Wanyue; Zevalkink, Alexandra; Kaduk, James A.; Nolas, George S.; California Polytechnic State University, San Luis Obispo; Department of Chemistry and Materials Science; National Institute of Standards and Technology NIST; University of Chicago; Michigan State University; Illinois Institute of Technology; University of South FloridaThermal expansion, lattice dynamics, heat capacity, compressibility, and pressure stability of the intermetallic clathrate Na24Si136 have been investigated by a combination of first-principles calculations and experimentation. Direct comparison of the properties of Na24Si136 with those of the low-density elemental modification Si136 provide insight into the effects of filling the silicon clathrate framework cages with Na on these properties. Calculations of the phonon dispersion only yield sensible results if the Na atoms in the large cages of the structure are displaced from the cage centers, but the exact nature of off-centering is difficult to elucidate conclusively. Pronounced peaks in the calculated phonon density of states for Na24Si136, absent for Si136, reflect the presence of low-energy vibrational modes associated with the guest atoms, in agreement with prior inelastic neutron-scattering experiments and reflected in marked temperature dependence of the guest atom atomic displacement parameters determined by single-crystal x-ray diffraction. The bulk modulus is only weakly influenced by filling the Si framework cages with Na, whereas the phase stability under pressure is significantly enhanced. The room-temperature linear coefficient of thermal expansion (CTE) is nearly a factor of 3 greater for Na24Si136 compared to Si136. Negative thermal expansion (NTE), observed in Si136 below 100 K, is noticeably absent in Na24Si136. In contrast to Si136, the thermal expansion behavior in Na24Si136 is relatively well described by the conventional Grüneisen-Debye model in the temperature range of 10-700 K. First-principles calculations in the quasiharmonic approximation correctly predict an increase in high-temperature CTE with Na loading, although the increase is less than observed in experiment. The calculations also fail to capture the absence of NTE in Na24Si136, perhaps due to anharmonic effects and/or inadequateness of the ordered structural model.Item Uncovering social-contextual and individual mental health factors associated with violence via computational inference(Elsevier, 2021-02-12) Santamaría-García, Hernando; Baez, Sandra; Aponte-Canencio, Diego Mauricio; Pasciarello, Guido Orlando; Donnelly-Kehoe, Patricio Andrés; Maggiotti, Gabriel; Matallana, Diana; Hesse, Eugenia; Neely, Alejandra; Zapata, José Gabriel; Chiong, Winston; Levy, Jonathan; Decety, Jean; Ibáñez, Agustín; Pontificia Universidad Javeriana Cali; Universidad de los Andes Colombia; Universidad Externado de Colombia; CONICET Rosario; ASAPP; Universidad de San Andrés; Universidad Adolfo Ibáñez; University of California San Francisco; Department of Neuroscience and Biomedical Engineering; University of ChicagoThe identification of human violence determinants has sparked multiple questions from different academic fields. Innovative methodological assessments of the weight and interaction of multiple determinants are still required. Here, we examine multiple features potentially associated with confessed acts of violence in ex-members of illegal armed groups in Colombia (N = 26,349) through deep learning and feature-derived machine learning. We assessed 162 social-contextual and individual mental health potential predictors of historical data regarding consequentialist, appetitive, retaliative, and reactive domains of violence. Deep learning yields high accuracy using the full set of determinants. Progressive feature elimination revealed that contextual factors were more important than individual factors. Combined social network adversities, membership identification, and normalization of violence were among the more accurate social-contextual factors. To a lesser extent the best individual factors were personality traits (borderline, paranoid, and antisocial) and psychiatric symptoms. The results provide a population-based computational classification regarding historical assessments of violence in vulnerable populations.