Zobrazeno 1 - 10
of 3 483
pro vyhledávání: '"A Flaxman"'
We develop the framework of Indirect Query Bayesian Optimization (IQBO), a new class of Bayesian optimization problems where the integrated feedback is given via a conditional expectation of the unknown function $f$ to be optimized. The underlying co
Externí odkaz:
http://arxiv.org/abs/2412.13559
Autor:
Yang, Fan, Ishida, Sahoko, Zhang, Mengyan, Jenson, Daniel, Mishra, Swapnil, Navott, Jhonathan, Flaxman, Seth
Remote sensing imagery offers rich spectral data across extensive areas for Earth observation. Many attempts have been made to leverage these data with transfer learning to develop scalable alternatives for estimating socio-economic conditions, reduc
Externí odkaz:
http://arxiv.org/abs/2411.14119
Autor:
Jenson, Daniel, Navott, Jhonathan, Zhang, Mengyan, Sharma, Makkunda, Semenova, Elizaveta, Flaxman, Seth
Stochastic processes model various natural phenomena from disease transmission to stock prices, but simulating and quantifying their uncertainty can be computationally challenging. For example, modeling a Gaussian Process with standard statistical me
Externí odkaz:
http://arxiv.org/abs/2411.12502
We study the problem of globally optimising a target variable of an unknown causal graph on which a sequence of soft or hard interventions can be performed. The problem of optimising the target variable associated with a causal graph is formalised as
Externí odkaz:
http://arxiv.org/abs/2411.03028
Autor:
Sharma, Makkunda, Yang, Fan, Vo, Duy-Nhat, Suel, Esra, Mishra, Swapnil, Bhatt, Samir, Fiala, Oliver, Rudgard, William, Flaxman, Seth
Satellite imagery has emerged as an important tool to analyse demographic, health, and development indicators. While various deep learning models have been built for these tasks, each is specific to a particular problem, with few standard benchmarks
Externí odkaz:
http://arxiv.org/abs/2407.05986
Model-based disease mapping remains a fundamental policy-informing tool in the fields of public health and disease surveillance. Hierarchical Bayesian models have emerged as the state-of-the-art approach for disease mapping since they are able to bot
Externí odkaz:
http://arxiv.org/abs/2305.19779
Autor:
Beth Flaxman, Elena K. Kupriyanova
Publikováno v:
Records of the Australian Museum, Iss 4, Pp 195-210 (2024)
Research voyages on board RV ‘Investigator’ between 2015 and 2022 sampled benthic communities of Australia’s Eastern and Southern continental margins from the slope down to abyssal depths (463–5000 m) as well as the seamounts off the Indian O
Externí odkaz:
https://doaj.org/article/7729e712780e43e4b5caef6d09e8e0a0
Autor:
Elena K. Kupriyanova, Beth Flaxman
Publikováno v:
Records of the Australian Museum, Vol 76, Iss 4, Pp 211-242 (2024)
Research voyages onboard RV ‘Investigator’ in 2021 (IN2021_V08) and 2022 (IN2022_V04) sampled benthic communities of seamounts off Christmas Island and Cocos (Keeling) Islands, also known as Indian Ocean Australian Territories (IOT). Over 150 spe
Externí odkaz:
https://doaj.org/article/85475fdc44914c0db0b430b0d69c360e
Autor:
Szi Kay Leung, Rosemary A. Bamford, Aaron R. Jeffries, Isabel Castanho, Barry Chioza, Christine S. Flaxman, Karen Moore, Emma L. Dempster, Joshua Harvey, Jonathan T. Brown, Zeshan Ahmed, Paul O’Neill, Sarah J. Richardson, Eilis Hannon, Jonathan Mill
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Increasing evidence suggests that alternative splicing plays an important role in Alzheimer’s disease (AD) pathology. We used long-read sequencing in combination with a novel bioinformatics tool (FICLE) to profile transcript diversity in t
Externí odkaz:
https://doaj.org/article/61f3ea0e8bfe4d4fbbcfd3346aaa8d89
Autor:
Semenova, Elizaveta, Verma, Prakhar, Cairney-Leeming, Max, Solin, Arno, Bhatt, Samir, Flaxman, Seth
Recent advances have shown that GP priors, or their finite realisations, can be encoded using deep generative models such as variational autoencoders (VAEs). These learned generators can serve as drop-in replacements for the original priors during MC
Externí odkaz:
http://arxiv.org/abs/2304.04307