Search Results - distributed evolution ((algorithm OR algorithmics) OR Algorithmsssic)

  1. 161
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  3. 163

    A Sparse Gaussian Process Framework for Photometric Redshift Estimation by Almosallam, Ibrahim A., Lindsay, Sam N., Jarvis, Matt J., Roberts, Stephen J.

    Published 2015
    Table of Contents: “… the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework…”
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  4. 164

    Shock waves in Interstellar Cloud-Cloud and Wind-Cloud Collisions by Navarrete, Sebastián, Pinargote, Bryan J., Banda-Barragán, Wladimir E.

    Published 2024
    Table of Contents: “… of the gas. We utilise our own python-based shock-finding algorithm to study the properties and distribution…”
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  5. 165

    Macroscopic Analysis of Vector Approximate Message Passing in a Model Mismatch Setting by Takahashi, Takashi, Kabashima, Yoshiyuki

    Published 2020
    Table of Contents: “…Vector approximate message passing (VAMP) is an efficient approximate inference algorithm used…”
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  6. 166

    Universality and Invariance in Hegselmann-Krause Opinion Dynamics: Proof of Three Conjectures by Molignini, Paolo

    Published 2025
    Table of Contents: “… distribution is always finite, guaranteeing that the algorithm for enumerating them terminates. The second…”
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  7. 167

    The Emergence of Grammar through Reinforcement Learning by Wechsler, Stephen, Shearer, James W., Erk, Katrin

    Published 2025
    Table of Contents: “…The evolution of grammatical systems of syntactic and semantic composition is modeled here with a…”
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  8. 168

    Environmental Effects on Galaxy Evolution by Mu, Ziqi

    Published 2025
    Table of Contents: “… approach does not require strong assumptions about the underlying distributional form and provides a more…”
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  9. 169

    Multi-species Dark Matter with Warmth and Randomness by Amin, Mustafa A., Delos, M. Sten, Yang, Kaixin

    Published 2025
    Table of Contents: “…We present a general analytic framework for the evolution of cosmic structure in multi-species dark…”
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  10. 170

    Star-forming environments in smoothed particle magnetohydrodynamics simulations II: Re-simulating isolated clumps to determine equivalence of extracted clumps and parent simulation... by Wurster, James, Rowan, Connar

    Published 2024
    Table of Contents: “… this, we modelled the evolution of 29 star forming clumps that were extracted from our previous simulations…”
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  11. 171

    Measurement of the Depth of Maximum of Air-Shower Profiles with energies between $\mathbf{10^{18.5}}$ and $\mathbf{10^{20}}$ eV using the Surface Detector of the Pierre Auger Obser... by The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., Zavrtanik, M.

    Published 2024
    Table of Contents: “… (1 EeV=$10^{18}$ eV) using the distributions of the depth of shower maximum $X_\mathrm{max…”
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  12. 172

    Inferring Change Points in High-Dimensional Regression via Approximate Message Passing by Arpino, Gabriel, Liu, Xiaoqi, Gontarek, Julia, Venkataramanan, Ramji

    Published 2024
    Table of Contents: “…) algorithm for estimating both the signals and the change point locations, and rigorously characterize its…”
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  13. 173

    Why Flow Matching is Particle Swarm Optimization? by Ouyang, Kaichen

    Published 2025
    Table of Contents: “… with the velocity update rules in PSO; both methods follow the fundamental framework of progressive evolution from…”
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  14. 174

    Wasserstein Evolution : Evolutionary Optimization as Phase Transition by Ouyang, Kaichen, Yu, Mingyang, Ke, Zong, Lian, Junbo Jacob, Fu, Shengwei, Hao, Xiaoyang, Yu, Shengju, Hu, Dayu

    Published 2025
    Table of Contents: “…Evolutionary algorithms (EAs) serve as powerful black-box optimizers inspired by biological…”
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    Constructing a Galaxy Cluster Catalog in IllustrisTNG-300 using the Mulguisin Algorithm by Shin, Lael, Sohn, Jubee, Ju, Young, Park, Inkyu, Sabiu, Cristiano G.

    Published 2024
    Table of Contents: “… the Mulguisin (MGS) algorithm to identify galaxy overdensities. Our cluster identification differs from…”
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  17. 177

    FedSem: A Resource Allocation Scheme for Federated Learning Assisted Semantic Communication by Zhou, Xinyu, Li, Yang, Zhao, Jun

    Published 2025
    Table of Contents: “…Semantic communication (SemCom), regarded as the evolution of the traditional Shannon…”
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  18. 178

    XDiag: Exact Diagonalization for Quantum Many-Body Systems by Wietek, Alexander, Staszewski, Luke, Ulaga, Martin, Ebert, Paul L., Karlsson, Hannes, Sarkar, Siddhartha, Shackleton, Leyna, Sinha, Aritra, Soares, Rafael D.

    Published 2025
    Table of Contents: “… software package designed to combine advanced and efficient algorithms for ED with and without symmetry…”
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  19. 179

    Learning to Evolve for Optimization via Stability-Inducing Neural Unrolling by Gao, Jiaxin, Liu, Yaohua, Cheng, Ran, Tan, Kay Chen

    Published 2025
    Table of Contents: “…Evolutionary algorithms serve as a powerful paradigm for tackling optimization challenges, yet…”
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  20. 180

    Fast pre-merger detection of massive black-hole binaries in LISA based on time-frequency excess power by Nobili, Francesco, Bellotti, Malvina, Buscicchio, Riccardo, Dotti, Massimo, Lupi, Alessandro

    Published 2026
    Table of Contents: “… by the quadrupole frequency evolution, we define a signal significance relative to a fitted background distribution…”
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