Zobrazeno 1 - 10
of 23 575
pro vyhledávání: '"Ashton, P."'
Autor:
Tang, Zhenwei, Jiao, Difan, McIlroy-Young, Reid, Kleinberg, Jon, Sen, Siddhartha, Anderson, Ashton
There are an increasing number of domains in which artificial intelligence (AI) systems both surpass human ability and accurately model human behavior. This introduces the possibility of algorithmically-informed teaching in these domains through more
Externí odkaz:
http://arxiv.org/abs/2409.20553
Autor:
Patel, Kajal, Shafiq, Zubair, Nogueira, Mateus, Menasché, Daniel Sadoc, Lovat, Enrico, Kashif, Taimur, Woiwood, Ashton, Martins, Matheus
Many organizations rely on Threat Intelligence (TI) feeds to assess the risk associated with security threats. Due to the volume and heterogeneity of data, it is prohibitive to manually analyze the threat information available in different loosely st
Externí odkaz:
http://arxiv.org/abs/2409.07709
Autor:
Cai, Xiaoyi, Queeney, James, Xu, Tong, Datar, Aniket, Pan, Chenhui, Miller, Max, Flather, Ashton, Osteen, Philip R., Roy, Nicholas, Xiao, Xuesu, How, Jonathan P.
Self-supervised learning is a powerful approach for developing traversability models for off-road navigation, but these models often struggle with inputs unseen during training. Existing methods utilize techniques like evidential deep learning to qua
Externí odkaz:
http://arxiv.org/abs/2409.03005
Autor:
Fischer, Tommy Z., Bradley, Ashton S.
We simulate the Gross-Pitaevskii equation to model the development of turbulence in a quantum fluid confined by a cuboid box potential, and forced by shaking along one axis. We observe the development of isotropic turbulence from anisotropic forcing
Externí odkaz:
http://arxiv.org/abs/2409.03184
Autor:
Tan, Ashton Yu Xuan, Yang, Yingkai, Zhang, Xiaofei, Li, Bowen, Gao, Xiaorong, Zheng, Sifa, Wang, Jianqiang, Gu, Xinyu, Li, Jun, Zhao, Yang, Zhang, Yuxin, Stathaki, Tania
Enhancing the safety of autonomous vehicles is crucial, especially given recent accidents involving automated systems. As passengers in these vehicles, humans' sensory perception and decision-making can be integrated with autonomous systems to improv
Externí odkaz:
http://arxiv.org/abs/2408.16315
The dominant practice of AI alignment assumes (1) that preferences are an adequate representation of human values, (2) that human rationality can be understood in terms of maximizing the satisfaction of preferences, and (3) that AI systems should be
Externí odkaz:
http://arxiv.org/abs/2408.16984
Autor:
Ashton, Neil, Mockett, Charles, Fuchs, Marian, Fliessbach, Louis, Hetmann, Hendrik, Knacke, Thilo, Schonwald, Norbert, Skaperdas, Vangelis, Fotiadis, Grigoris, Walle, Astrid, Hupertz, Burkhard, Maddix, Danielle
Machine Learning (ML) has the potential to revolutionise the field of automotive aerodynamics, enabling split-second flow predictions early in the design process. However, the lack of open-source training data for realistic road cars, using high-fide
Externí odkaz:
http://arxiv.org/abs/2408.11969
Autor:
Krause, Nils A., Bradley, Ashton S.
Homogeneous planar superfluids exhibit a range of low-energy excitations that also appear in highly excited states like superfluid turbulence. In dilute gas Bose-Einstein condensates, the Jones- Roberts soliton family includes vortex dipoles and rare
Externí odkaz:
http://arxiv.org/abs/2408.06532
The development of Machine Learning (ML) methods for Computational Fluid Dynamics (CFD) is currently limited by the lack of openly available training data. This paper presents a new open-source dataset comprising of high fidelity, scale-resolving CFD
Externí odkaz:
http://arxiv.org/abs/2407.20801
Autor:
Ashton, Neil, Angel, Jordan B., Ghate, Aditya S., Kenway, Gaetan K. W., Wong, Man Long, Kiris, Cetin, Walle, Astrid, Maddix, Danielle C., Page, Gary
This paper presents a new open-source high-fidelity dataset for Machine Learning (ML) containing 355 geometric variants of the Windsor body, to help the development and testing of ML surrogate models for external automotive aerodynamics. Each Computa
Externí odkaz:
http://arxiv.org/abs/2407.19320