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pro vyhledávání: '"Gleeson, P"'
Autor:
Glaze, Nicholas, McNeely, Tria, Zhu, Yiwen, Gleeson, Matthew, Serr, Helen, Bhopi, Rajeev, Krishnan, Subru
Publikováno v:
Proc. ACM Manag. Data, Vol. 2, No. 3 (SIGMOD), Article 149. Publication date: June 2024
Cloud operators have expanded their service offerings, known as Stock Keeping Units (SKUs), to accommodate diverse demands, resulting in increased complexity for customers to select appropriate configurations. In a studied system, only 43% of the res
Externí odkaz:
http://arxiv.org/abs/2411.11325
Self-reinforcing cascades: A spreading model for beliefs or products of varying intensity or quality
Autor:
Hébert-Dufresne, Laurent, Lovato, Juniper, Burgio, Giulio, Gleeson, James P., Redner, S., Krapivsky, P. L.
Models of how things spread often assume that transmission mechanisms are fixed over time. However, social contagions--the spread of ideas, beliefs, innovations--can lose or gain in momentum as they spread: ideas can get reinforced, beliefs strengthe
Externí odkaz:
http://arxiv.org/abs/2411.00714
Autor:
Yeung, Kylie, Gleeson, Fergus V, Schulte, Rolf F, McIntyre, Anthony, Serres, Sebastien, Morris, Peter, Auer, Dorothee, Tyler, Damian J, Grist, James T, Wiesinger, Florian
Purpose: To present a novel generalized MR image reconstruction based on pseudoinversion of the encoding matrix (Pinv-Recon) as a simple yet powerful method, and demonstrate its computational feasibility for diverse MR imaging applications. Methods:
Externí odkaz:
http://arxiv.org/abs/2410.06129
Long COVID is characterized by persistent symptoms, particularly pulmonary impairment, which necessitates advanced imaging for accurate diagnosis. Hyperpolarised Xenon-129 MRI (XeMRI) offers a promising avenue by visualising lung ventilation, perfusi
Externí odkaz:
http://arxiv.org/abs/2406.15172
Autor:
Thapa, Kamal, Iadlovska, Olena S., Basnet, Bijaya, Wang, Hao, Paul, Ayusha, Gleeson, James T., Lavrentovich, Oleg D.
We explore the structure and magnetic field response of edge dislocations in Grandjean-Cano wedge cells filled with chiral mixtures of the ferroelectric nematic mesogen DIO. Upon cooling, the ordering changes from paraelectric in the cholesteric phas
Externí odkaz:
http://arxiv.org/abs/2403.20229
Neural networks sometimes exhibit grokking, a phenomenon where perfect or near-perfect performance is achieved on a validation set well after the same performance has been obtained on the corresponding training set. In this workshop paper, we introdu
Externí odkaz:
http://arxiv.org/abs/2402.08946
Spontaneous symmetry breaking and emergent polar order are each of fundamental importance to a range of scientific disciplines, as well as generating rich phase behaviour in liquid crystals (LCs). Here, we show the union of these phenomena to lead to
Externí odkaz:
http://arxiv.org/abs/2402.07305
An algorithm for efficiently calculating the expected size of single-seed cascade dynamics on networks is proposed and tested. The expected size is a time-dependent quantity and so enables the identification of nodes who are the most influential earl
Externí odkaz:
http://arxiv.org/abs/2401.16978
Autor:
Yang, Jiacheng, Giannoula, Christina, Wu, Jun, Elhoushi, Mostafa, Gleeson, James, Pekhimenko, Gennady
Sparse Convolution (SC) is widely used for processing 3D point clouds that are inherently sparse. Different from dense convolution, SC preserves the sparsity of the input point cloud by only allowing outputs to specific locations. To efficiently comp
Externí odkaz:
http://arxiv.org/abs/2401.06145
The ferroelectric nematic phase (NF) is a recently discovered phase of matter in which the orientational order of the conventional nematic liquid crystal state is augmented with polar order. Atomistic simulations suggest that the polar NF phase would
Externí odkaz:
http://arxiv.org/abs/2309.14161