Zobrazeno 1 - 10
of 7 334
pro vyhledávání: '"Hellsten"'
Autor:
Hellsten Laura
Publikováno v:
Open Philosophy, Vol 5, Iss 1, Pp 474-489 (2022)
This is a meta-reflection on the methodological and epistemological challenges of doing ethnographic theology in a context outside the church or religious communities. Particularly, it argues that in a multi- or inter-disciplinary setting theologians
Externí odkaz:
https://doaj.org/article/8390f257832d4ceaae0f546ef2a19c52
Autor:
Bean, Andrew M., Hellsten, Simi, Mayne, Harry, Magomere, Jabez, Chi, Ethan A., Chi, Ryan, Hale, Scott A., Kirk, Hannah Rose
In this paper, we present the LingOly benchmark, a novel benchmark for advanced reasoning abilities in large language models. Using challenging Linguistic Olympiad puzzles, we evaluate (i) capabilities for in-context identification and generalisation
Externí odkaz:
http://arxiv.org/abs/2406.06196
Autor:
Brännström, Martin, Hellsten, Isabelle
This study investigates the effects of the digital marketing channels Search engine optimization (SEO) and SEM, focusing on Google Ads, in the context of the consumer decision funnel in the Swedish market. This was done through a single-case study wi
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-226188
Autor:
Hellsten, Simon
This bachelor's thesis in Computer Science explores the efficiency of an incremental re-tokenization algorithm in the context of BPE-trained SentencePiece models used in natural language processing. The thesis begins by underscoring the critical role
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-221890
Autor:
Hellsten Laura, des Bouvrie Nicole
Publikováno v:
Open Philosophy, Vol 4, Iss 1, Pp 372-373 (2021)
Externí odkaz:
https://doaj.org/article/e1baa273c5ec4d70b8eac93b8963c3ad
Publikováno v:
International Conference on Machine Learning, 2024
High-dimensional problems have long been considered the Achilles' heel of Bayesian optimization algorithms. Spurred by the curse of dimensionality, a large collection of algorithms aim to make it more performant in this setting, commonly by imposing
Externí odkaz:
http://arxiv.org/abs/2402.02229
We develop methods to show that infinite-dimensional modules over the Iwasawa algebra $KG$ of a uniform pro-p group are faithful and apply them to show that the metaplectic representation for the symplectic group is faithful.
Comment: 17 pages,
Comment: 17 pages,
Externí odkaz:
http://arxiv.org/abs/2401.04581
Diffusion models currently dominate the field of data-driven image synthesis with their unparalleled scaling to large datasets. In this paper, we identify and rectify several causes for uneven and ineffective training in the popular ADM diffusion mod
Externí odkaz:
http://arxiv.org/abs/2312.02696
Bayesian optimization is an effective method for optimizing expensive-to-evaluate black-box functions. High-dimensional problems are particularly challenging as the surrogate model of the objective suffers from the curse of dimensionality, which make
Externí odkaz:
http://arxiv.org/abs/2310.03515