Zobrazeno 1 - 10
of 29 788
pro vyhledávání: '"Mattei, A. A."'
This work presents the existence and uniqueness of solution to a free boundary value problem related to biofilm growth. The problem consists of a system of nonlinear hyperbolic partial differential equations governing the microbial species growth, an
Externí odkaz:
http://arxiv.org/abs/2411.17974
We present the stability analysis of two free boundary problems arising in biofilm modelling. The first, introduced in the 1980s by Wanner and Gujer, is related to the competition between autotrophic and heterotrophic bacteria in a biofilm bioreactor
Externí odkaz:
http://arxiv.org/abs/2411.16977
We introduce and study the analytic relative Jacobian sheaf for a Lagrangian fibration of a hyperk\"ahler manifold. When the fibration has irreducible fibers in codimension 1 and a relative principal polarization, we show that it is isomorphic to the
Externí odkaz:
http://arxiv.org/abs/2411.01953
Autor:
Aird, Amanda, Štefancová, Elena, All, Cassidy, Voida, Amy, Homola, Martin, Mattei, Nicholas, Burke, Robin
Algorithmic fairness in recommender systems requires close attention to the needs of a diverse set of stakeholders that may have competing interests. Previous work in this area has often been limited by fixed, single-objective definitions of fairness
Externí odkaz:
http://arxiv.org/abs/2410.04551
Autor:
Stefancova, Elena, All, Cassidy, Paup, Joshua, Homola, Martin, Mattei, Nicholas, Burke, Robin
Synthetic data is a useful resource for algorithmic research. It allows for the evaluation of systems under a range of conditions that might be difficult to achieve in real world settings. In recommender systems, the use of synthetic data is somewhat
Externí odkaz:
http://arxiv.org/abs/2409.14078
Aggregating the preferences of multiple agents into a collective decision is a common step in many important problems across areas of computer science including information retrieval, reinforcement learning, and recommender systems. As Social Choice
Externí odkaz:
http://arxiv.org/abs/2408.13630
Autor:
Villa, Irene, Monguzzi, Angelo, Lorenzi, Roberto, Orfano, Matteo, Babin, Vladimir, Hájek, František, Kuldová, Karla, Kučerková, Romana, Beitlerová, Alena, Mattei, Ilaria, Buresova, Hana, Pjatkan, Radek, Čuba, Václav, Procházková, Lenka Prouzová, Nikl, Martin
Fast emitting polymeric scintillators are requested in advanced applications where high-speed detectors with large signal-to-noise ratio are needed. However, their low density implies a weak stopping power of high energy radiations, thus a limited li
Externí odkaz:
http://arxiv.org/abs/2408.01340
Autor:
Luo, Xusheng, Wei, Tianhao, Liu, Simin, Wang, Ziwei, Mattei-Mendez, Luis, Loper, Taylor, Neighbor, Joshua, Hutchison, Casidhe, Liu, Changliu
This work addresses the certification of the local robustness of vision-based two-stage 6D object pose estimation. The two-stage method for object pose estimation achieves superior accuracy by first employing deep neural network-driven keypoint regre
Externí odkaz:
http://arxiv.org/abs/2408.00117
Autor:
Mattei, Dominique, Meinsma, Reinder
We investigate obstruction classes of moduli spaces of sheaves on K3 surfaces. We extend previous results by Caldararu, explicitly determining the obstruction class and its order in the Brauer group. Our main theorem establishes a short exact sequenc
Externí odkaz:
http://arxiv.org/abs/2404.16652
Trees are convenient models for obtaining explainable predictions on relatively small datasets. Although there are many proposals for the end-to-end construction of such trees in supervised learning, learning a tree end-to-end for clustering without
Externí odkaz:
http://arxiv.org/abs/2402.12232