Suchergebnisse - distributed evolution (algorithm OR (algorithmics OR Algorithmssicics))

  1. 161
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  3. 163

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

    Veröffentlicht 2015
    Inhaltsangabe: “… 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 von Navarrete, Sebastián, Pinargote, Bryan J., Banda-Barragán, Wladimir E.

    Veröffentlicht 2024
    Inhaltsangabe: “… 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 von Takahashi, Takashi, Kabashima, Yoshiyuki

    Veröffentlicht 2020
    Inhaltsangabe: “… 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 von Molignini, Paolo

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Wechsler, Stephen, Shearer, James W., Erk, Katrin

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Mu, Ziqi

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Amin, Mustafa A., Delos, M. Sten, Yang, Kaixin

    Veröffentlicht 2025
    Inhaltsangabe: “… 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... von Wurster, James, Rowan, Connar

    Veröffentlicht 2024
    Inhaltsangabe: “… 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... von 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.

    Veröffentlicht 2024
    Inhaltsangabe: “… (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 von Arpino, Gabriel, Liu, Xiaoqi, Gontarek, Julia, Venkataramanan, Ramji

    Veröffentlicht 2024
    Inhaltsangabe: “… ) 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? von Ouyang, Kaichen

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Ouyang, Kaichen, Yu, Mingyang, Ke, Zong, Lian, Junbo Jacob, Fu, Shengwei, Hao, Xiaoyang, Yu, Shengju, Hu, Dayu

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Shin, Lael, Sohn, Jubee, Ju, Young, Park, Inkyu, Sabiu, Cristiano G.

    Veröffentlicht 2024
    Inhaltsangabe: “… 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 von Zhou, Xinyu, Li, Yang, Zhao, Jun

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Wietek, Alexander, Staszewski, Luke, Ulaga, Martin, Ebert, Paul L., Karlsson, Hannes, Sarkar, Siddhartha, Shackleton, Leyna, Sinha, Aritra, Soares, Rafael D.

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Gao, Jiaxin, Liu, Yaohua, Cheng, Ran, Tan, Kay Chen

    Veröffentlicht 2025
    Inhaltsangabe: “… 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 von Nobili, Francesco, Bellotti, Malvina, Buscicchio, Riccardo, Dotti, Massimo, Lupi, Alessandro

    Veröffentlicht 2026
    Inhaltsangabe: “… by the quadrupole frequency evolution, we define a signal significance relative to a fitted background distribution …”
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