Zobrazeno 1 - 10
of 1 361
pro vyhledávání: '"Duncan Andrew"'
Energy-based models (EBMs) offer a flexible framework for probabilistic modelling across various data domains. However, training EBMs on data in discrete or mixed state spaces poses significant challenges due to the lack of robust and fast sampling m
Externí odkaz:
http://arxiv.org/abs/2412.01019
Selecting cost-effective optimal sensor configurations for subsequent inference of parameters in black-box stochastic systems faces significant computational barriers. We propose a novel and robust approach, modelling the joint distribution over inpu
Externí odkaz:
http://arxiv.org/abs/2410.12036
Global trade is shaped by a complex mix of factors beyond supply and demand, including tangible variables like transport costs and tariffs, as well as less quantifiable influences such as political and economic relations. Traditionally, economists mo
Externí odkaz:
http://arxiv.org/abs/2409.06554
Autor:
Catia Correia-Caeiro, Anne Burrows, Duncan Andrew Wilson, Abdelhady Abdelrahman, Takako Miyabe-Nishiwaki
Publikováno v:
PLoS ONE, Vol 17, Iss 5, p e0266442 (2022)
Facial expressions are subtle cues, central for communication and conveying emotions in mammals. Traditionally, facial expressions have been classified as a whole (e.g. happy, angry, bared-teeth), due to automatic face processing in the human brain,
Externí odkaz:
https://doaj.org/article/61d01f53db3d440b9a1e08165643e34c
Publikováno v:
PLoS ONE, Vol 16, Iss 5, p e0251488 (2021)
Research funding is an important factor for public science. Funding may affect which research topics get addressed, and what research outputs are produced. However, funding has often been studied simplistically, using top-down or system-led perspecti
Externí odkaz:
https://doaj.org/article/f12217e8c9e84f93b072fa2e663a94b1
Autor:
Bull, Lawrence A., Jeon, Chiho, Girolami, Mark, Duncan, Andrew, Schooling, Jennifer, Haro, Miguel Bravo
We suggest a multilevel model, to represent aggregate train-passing events from the Staffordshire bridge monitoring system. We formulate a combined model from simple units, representing strain envelopes (of each train passing) for two types of commut
Externí odkaz:
http://arxiv.org/abs/2403.17820
Structural Health Monitoring (SHM) technologies offer much promise to the risk management of the built environment, and they are therefore an active area of research. However, information regarding material properties, such as toughness and strength
Externí odkaz:
http://arxiv.org/abs/2309.07695
Training energy-based models (EBMs) on discrete spaces is challenging because sampling over such spaces can be difficult. We propose to train discrete EBMs with energy discrepancy (ED), a novel type of contrastive loss functional which only requires
Externí odkaz:
http://arxiv.org/abs/2307.07595