Risultati della ricerca - distributed evolution ((algorithm OR algorithmics) OR (algorithmics OR Algorithmsssicics))

Multi-Objective Optimization for Synthetic-to-Real Style Transfer di Chigot, Estelle, Oberlin, Thomas, Huguenin, Manon, Wilson, Dennis

Sommario: “... genetic algorithms, we optimize pipelines to balance structural coherence and style similarity to target...”
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Learning Density Evolution from Snapshot Data di Yao, Rentian, Nitanda, Atsushi, Chen, Xiaohui, Yang, Yun

Sommario: “... distribution-on-scalar regression approach for estimating the density evolution of a stochastic process from...”
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Dynamic angular synchronization under smoothness constraints di Araya, Ernesto, Cucuringu, Mihai, Tyagi, Hemant

Sommario: “... smoothness condition on the evolution of the latent angles, we derive three algorithms for joint estimation...”
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Learning Low-Dimensional Strain Models of Soft Robots by Looking at the Evolution of Their Shape with Application to Model-Based Control di Valadas, Ricardo, Stölzle, Maximilian, Liu, Jingyue, Della Santina, Cosimo

Sommario: “... with an algorithm that uses image data (i.e., shape evolutions) to determine the minimal necessary segments...”
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Monte Carlo simulations of drop growth by coalescence and collision-induced breakup di L. Alfonso

Sommario: “... simulation A Monte Carlo framework to simulate the evolution of drop spectra by coalescence and collision...”
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QoS‐enhanced load balancing strategies for metaverse‐infused VR/AR in engineering education 5.0 di Kiran Deep Singh, Prabh Deep Singh

Sommario: “... Kiran Deep Singh Prabh Deep Singh Computer Applications in Engineering Education AbstractThe evolution...”
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Eco-geomorphic modelling response of tidal marshes to sea level rise and changes in suspended sediment supply. di Egidazu-de la Parte, Beñat, Balbi, Stefano, Villa, Ferdinando, Bengochea, Diego, Curcio, Andrea Celeste, Galván, Cristina, González, Carlos J, Juanes, José A, Ondiviela, Bárbara, Peralta, Gloria, Puente, Araceli, Ramos, Elvira, Rodríguez-Rojo, Concepción N, Pascual, Marta

Sommario: “... concentrations, the evolution of these systems has gained special attention across scientific fields. Several...”
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Macroscopic Analysis of Vector Approximate Message Passing in a Model Mismatch Setting di Takahashi, Takashi, Kabashima, Yoshiyuki

Sommario: “...Vector approximate message passing (VAMP) is an efficient approximate inference algorithm used...”
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Universality and Invariance in Hegselmann-Krause Opinion Dynamics: Proof of Three Conjectures di Molignini, Paolo

Sommario: “... distribution is always finite, guaranteeing that the algorithm for enumerating them terminates. The second...”
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Bayesian inference of mixed Gaussian phylogenetic models di Brahmantio, Bayu, Bartoszek, Krzysztof, Yapar, Etka

Sommario: “...Background: Continuous traits evolution of a group of taxa that are correlated through a...”
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Euclid preparation. XXXI. The effect of the variations in photometric passbands on photometric-redshift accuracy di Euclid Collaboration, Paltani, Stéphane, Coupon, J., Hartley, W. G., Alvarez-Ayllon, A., Dubath, F., Mohr, J. J., Schirmer, M., Cuillandre, J. -C., Desprez, G., Ilbert, O., Kuijken, K., Aghanim, N., Altieri, B., Amara, A., Auricchio, N., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Cardone, V. F., Carretero, J., Castander, F. J., Castellano, M., Cavuoti, S., Cledassou, R., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Cropper, M., Da Silva, A., Degaudenzi, H., Dinis, J., Douspis, M., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Grazian, A., Haugan, S. V., Hoekstra, H., Hornstrup, A., Hudelot, P., Jahnke, K., Kümmel, M., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Nightingale, J., Padilla, C., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Surace, C., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zamorani, G., Zoubian, J., Andreon, S., Aussel, H., Bardelli, S., Bolzonella, M., Boucaud, A., Di Ferdinando, D., Farina, M., Graciá-Carpio, J., Lindholm, V., Maino, D., Mauri, N., Neissner, C., Scottez, V., Zucca, E., Baccigalupi, C., Ballardini, M., Biviano, A., Blanchard, A., Borgani, S., Borlaff, A. S., Burigana, C., Cabanac, R., Cappi, A., Carvalho, C. S., Casas, S., Castignani, G., Chambers, K., Cooray, A. R., Courtois, H. M., Cucciati, O., Davini, S., De Lucia, G., Dole, H., Escartin, J. A., Escoffier, S., Finelli, F., Fotopoulou, S., Ganga, K., George, K., Gozaliasl, G., Hildebrandt, H., Hook, I., Muñoz, A. Jimenez, Joachimi, B., Kansal, V., Keihanen, E., Kirkpatrick, C. C., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Maoli, R., Marcin, S., Martinelli, M., Martinet, N., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Patrizii, L., Pollack, J. E., Popa, V., Porciani, C., Potter, D., Pourtsidou, A., Pozzetti, L., Pöntinen, M., Reimberg, P., Sánchez, A. G., Sakr, Z., Sefusatti, E., Sereno, M., Mancini, A. Spurio, Stadel, J., Steinwagner, J., Teyssier, R., Valieri, C., Valiviita, J., van Mierlo, S. E., Veropalumbo, A., Viel, M., Weaver, J. R.

Sommario: “... extragalactic surveys. While the requirements on photo-zs for the study of galaxy evolution mostly pertain...”
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Accelerating FRB Search: Dataset and Methods di Guo, Xuerong, Wang, Han, Xiao, Yifan, Chen, Huaxi, Ke, Yinan, Miao, ChenChen, Wang, Pei, Li, Di, Jin, Chenwu, He, Ling, Feng, Yi, Zhang, Yongkun, Xu, Jiaying, Chen, Guangyong

Sommario: “... in studying the distribution and evolution of matter in the universe. FRBs can only be observed through radio...”
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Environmental Effects on Galaxy Evolution di Mu, Ziqi

Sommario: “... approach does not require strong assumptions about the underlying distributional form and provides a more...”
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Multi-species Dark Matter with Warmth and Randomness di Amin, Mustafa A., Delos, M. Sten, Yang, Kaixin

Sommario: “...We present a general analytic framework for the evolution of cosmic structure in multi-species dark...”
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Exact Solutions to the Quantum Schrödinger Bridge Problem di Bordyuh, Mykola, Clevert, Djork-Arné, Bertolini, Marco

Sommario: “...The Quantum Schrödinger Bridge Problem (QSBP) describes the evolution of a stochastic process...”
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Generalized Incremental Learning under Concept Drift across Evolving Data Streams di Yu, En, Lu, Jie, Zhang, Guangquan

Sommario: “... shifts, they overlook the critical co-evolution of label spaces and distributions under limited...”
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Simulation of pulsed dynamic nuclear polarization in the steady state di Jegadeesan, Shebha Anandhi, Zhao, Yujie, Smith, Graham M., Kuprov, Ilya, Mathies, Guinevere

Sommario: “... and nuclear relaxation. In this article, we explore three algorithms to compute this stroboscopic steady state...”
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Mitigating Modality Quantity and Quality Imbalance in Multimodal Online Federated Learning di Wang, Heqiang, Yang, Weihong, Zhong, Xiaoxiong, Zhou, Jia, Liu, Fangming, Zhang, Weizhe

Sommario: “... processing of heterogeneous multimodal data. This evolution necessitates distributed learning paradigms...”
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A Unifying View of Coverage in Linear Off-Policy Evaluation di Amortila, Philip, Huang, Audrey, Krishnamurthy, Akshay, Jiang, Nan

Sommario: “... distribution. While such guarantees are well-understood for several popular algorithms under stronger...”
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FastBUS: A Fast Bayesian Framework for Unified Weakly-Supervised Learning di Wang, Ziquan, Wang, Haobo, Chen, Ke, Feng, Lei, Chen, Gang

Sommario: “... framework that efficiently infers latent true label distributions across various weak supervisions. Our key...”
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