Zobrazeno 1 - 10
of 19 678
pro vyhledávání: '"Ericsson, A."'
Autor:
Ghorai, Sagar, Clulow, Rebecca, Cedervall, Johan, Huang, Shuo, Ericsson, Tore, Häggström, Lennart, Skini, Ridha, Shtender, Vitalii, Vitos, Levente, Eriksson, Olle, Scheibel, Franziska, Gutfleisch, Oliver, Sahlberg, Martin, Svedlindh, Peter
The non-stoichiometric Fe$_2$P-type (FeMnP$_{0.5}$Si$_{0.5}$)$_{1-x}$(FeV)$_{x}$ alloys ( $x=0, 0.01$, $0.02$, and $0.03$) have been investigated as potential candidates for magnetic refrigeration near room temperature. The magnetic ordering temperat
Externí odkaz:
http://arxiv.org/abs/2410.01747
The use of Thin-foil Proton Recoil (TPR) spectrometers for application in neutron spectroscopy is of high relevance for future fusion devices such as ITER, where neutron spectroscopy will play a crucial role in fuel content monitoring. Existing resea
Externí odkaz:
http://arxiv.org/abs/2408.16093
Autor:
Ericsson, Linus, Espinosa, Miguel, Yang, Chenhongyi, Antoniou, Antreas, Storkey, Amos, Cohen, Shay B., McDonagh, Steven, Crowley, Elliot J.
Neural architecture search (NAS) finds high performing networks for a given task. Yet the results of NAS are fairly prosaic; they did not e.g. create a shift from convolutional structures to transformers. This is not least because the search spaces i
Externí odkaz:
http://arxiv.org/abs/2405.20838
In continual learning (CL) -- where a learner trains on a stream of data -- standard hyperparameter optimisation (HPO) cannot be applied, as a learner does not have access to all of the data at the same time. This has prompted the development of CL-s
Externí odkaz:
http://arxiv.org/abs/2404.06466
Autor:
Yang, Chenhongyi, Chen, Zehui, Espinosa, Miguel, Ericsson, Linus, Wang, Zhenyu, Liu, Jiaming, Crowley, Elliot J.
We present PlainMamba: a simple non-hierarchical state space model (SSM) designed for general visual recognition. The recent Mamba model has shown how SSMs can be highly competitive with other architectures on sequential data and initial attempts hav
Externí odkaz:
http://arxiv.org/abs/2403.17695
In-ice radio-detection is a promising technique to discover and characterize ultra-high-energy (UHE) neutrinos, with energies above 100 PeV, adopted by present - ARA, ARIANNA, and RNO-G - and planned - IceCube-Gen2. So far, their ability to measure n
Externí odkaz:
http://arxiv.org/abs/2402.02432
The reliability with Machine Learning (ML) techniques in novel materials discovery often depend on the quality of the dataset, in addition to the relevant features used in describing the material. In this regard, the current study presents and valida
Externí odkaz:
http://arxiv.org/abs/2312.11335
Autor:
Ericsson, Leon, Hjalmarsson, Adam, Akbar, Muhammad Usman, Ferdian, Edward, Bonini, Mia, Hardy, Brandon, Schollenberger, Jonas, Aristova, Maria, Winter, Patrick, Burris, Nicholas, Fyrdahl, Alexander, Sigfridsson, Andreas, Schnell, Susanne, Figueroa, C. Alberto, Nordsletten, David, Young, Alistair A., Marlevi, David
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of traine
Externí odkaz:
http://arxiv.org/abs/2311.11819
Autor:
Eastwood, Cian, von Kügelgen, Julius, Ericsson, Linus, Bouchacourt, Diane, Vincent, Pascal, Schölkopf, Bernhard, Ibrahim, Mark
Self-supervised representation learning often uses data augmentations to induce some invariance to "style" attributes of the data. However, with downstream tasks generally unknown at training time, it is difficult to deduce a priori which attributes
Externí odkaz:
http://arxiv.org/abs/2311.08815
Distribution shifts are all too common in real-world applications of machine learning. Domain adaptation (DA) aims to address this by providing various frameworks for adapting models to the deployment data without using labels. However, the domain sh
Externí odkaz:
http://arxiv.org/abs/2309.03879