Zobrazeno 1 - 10
of 916 572
pro vyhledávání: '"An, Julie"'
Autor:
Gravier, Julie, Barthelemy, Marc
Publikováno v:
Nature Cities, Volume 1 September 2024, 567-575
Contemporary literature on the dynamics of economic activities in growing cities mainly focused on a few years or decades time frames. Using a new geo-historical database constructed from historical directories with about 1 million entries, we presen
Externí odkaz:
http://arxiv.org/abs/2409.03263
Autor:
Kepner, Jeremy, Jananthan, Hayden, Jones, Michael, Arcand, William, Bestor, David, Bergeron, William, Burrill, Daniel, Buluc, Aydin, Byun, Chansup, Davis, Timothy, Gadepally, Vijay, Grant, Daniel, Houle, Michael, Hubbell, Matthew, Luszczek, Piotr, Milechin, Lauren, Milner, Chasen, Morales, Guillermo, Morris, Andrew, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Wachman, Gabriel, Yee, Charles, Michaleas, Peter
Understanding what is normal is a key aspect of protecting a domain. Other domains invest heavily in observational science to develop models of normal behavior to better detect anomalies. Recent advances in high performance graph libraries, such as t
Externí odkaz:
http://arxiv.org/abs/2409.03111
Autor:
Schwerdtner, Paul, Mohan, Prakash, Pachalieva, Aleksandra, Bessac, Julie, O'Malley, Daniel, Peherstorfer, Benjamin
This work introduces an online greedy method for constructing quadratic manifolds from streaming data, designed to enable in-situ analysis of numerical simulation data on the Petabyte scale. Unlike traditional batch methods, which require all data to
Externí odkaz:
http://arxiv.org/abs/2409.02703
Autor:
Zhao, Zhanyue, Szewczyk, Benjamin, Tarasek, Matthew, Bales, Charles, Wang, Yang, Liu, Ming, Jiang, Yiwei, Bhushan, Chitresh, Fiveland, Eric, Campwala, Zahabiya, Trowbridge, Rachel, Johansen, Phillip M., Olmsted, Zachary, Ghoshal, Goutam, Heffter, Tamas, Gandomi, Katie, Tavakkolmoghaddam, Farid, Nycz, Christopher, Jeannotte, Erin, Mane, Shweta, Nalwalk, Julia, Burdette, E. Clif, Qian, Jiang, Yeo, Desmond, Pilitsis, Julie, Fischer, Gregory S.
Intracorporeal needle-based therapeutic ultrasound (NBTU) is a minimally invasive option for intervening in malignant brain tumors, commonly used in thermal ablation procedures. This technique is suitable for both primary and metastatic cancers, util
Externí odkaz:
http://arxiv.org/abs/2409.02395
In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under physiological conditions. Since then the biophysics community has made si
Externí odkaz:
http://arxiv.org/abs/2409.02240
Autor:
Shaaban, Tamara, Oher, Hanna, Aupiais, Jean, Champion, Julie, Gomes, André Severo Pereira, Naour, Claire Le, Maloubier, Melody, Réal, Florent, Renault, Eric, Rocquefelte, Xavier, Siberchicot, Bruno, Vallet, Valérie, Maurice, Rémi
The bond distance is the simplest and most obvious indicator of the nature of a given chemical bond. However, for rare chemistry, it may happen that it is not yet firmly established. In this communication, we will show that the formally-triple protac
Externí odkaz:
http://arxiv.org/abs/2409.01338
Autor:
Vogel, Mathias, Tateno, Keisuke, Pollefeys, Marc, Tombari, Federico, Rakotosaona, Marie-Julie, Engelmann, Francis
In this work, we tackle the task of point cloud denoising through a novel framework that adapts Diffusion Schr\"odinger bridges to points clouds. Unlike previous approaches that predict point-wise displacements from point features or learned noise di
Externí odkaz:
http://arxiv.org/abs/2408.16325
This work develops an efficient real-time inverse formulation for inferring the aerodynamic surface pressures on a hypersonic vehicle from sparse measurements of the structural strain. The approach aims to provide real-time estimates of the aerodynam
Externí odkaz:
http://arxiv.org/abs/2408.15286
Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This method replaces the integral representation of a shift-invariant kernel
Externí odkaz:
http://arxiv.org/abs/2408.13231
Biclustering is an unsupervised machine-learning approach aiming to cluster rows and columns simultaneously in a data matrix. Several biclustering algorithms have been proposed for handling numeric datasets. However, real-world data mining problems o
Externí odkaz:
http://arxiv.org/abs/2408.13217