Zobrazeno 1 - 10
of 1 006
pro vyhledávání: '"Raatikainen P"'
Publikováno v:
Phys. Rev. Lett. 133, 121403 (2024)
We study the formation of primordial black holes (PBH) with ultra-slow-roll inflation when stochastic effects are important. We use the $\Delta N$ formalism and simplify the stochastic equations with an analytical constant-roll approximation. Conside
Externí odkaz:
http://arxiv.org/abs/2312.12911
Autor:
Anna M. E. Noten, Tamas Szili-Torok, Sabine Ernst, David Burkhardt, Diogo Cavaco, Xu Chen, Jim W. Cheung, Christian de Chillou, Eugene Crystal, Daniel H. Cooper, Maurizio Gasparini, Tamas Geczy, Konrad Goehl, Burkhard Hügl, Qi Jin, Priit Kampus, Pedram Kazemian, Muchtiar Khan, Ole Kongstad, Jarkko Magga, Darren Peress, Pekka Raatikainen, Alexander Romanov, Ole Rossvoll, Gurjit Singh, Radu Vatasescu, Sip Wijchers, Kohei Yamashiro, Sing-Chien Yap, J. Peter Weiss
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 11 (2024)
PreambleRobotic magnetic navigation (RMN)-guided catheter ablation (CA) technology has been used for the treatment of cardiac arrhythmias for almost 20 years. Various studies reported that RMN allows for high catheter stability, improved lesion forma
Externí odkaz:
https://doaj.org/article/18964276adb54b92b6bf57d725058bf8
Autor:
Raatikainen, Lassi, Rahtu, Esa
The objective of this paper is to assess the quality of explanation heatmaps for image classification tasks. To assess the quality of explainability methods, we approach the task through the lens of accuracy and stability. In this work, we make the f
Externí odkaz:
http://arxiv.org/abs/2208.06175
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 5, Pp 542-552 (2024)
Deep neural networks bear substantial cloud computational loads and often surpass client devices' capabilities. Research has concentrated on reducing the inference burden of convolutional neural networks processing images. Unstructured pruning, which
Externí odkaz:
https://doaj.org/article/d3877c3d230a41d2aaf6cf301b5273c4
Autor:
K. Nordling, J.-P. Keskinen, S. Romakkaniemi, H. Kokkola, P. Räisänen, A. Lipponen, A.-I. Partanen, J. Ahola, J. Tonttila, M. E. Alper, H. Korhonen, T. Raatikainen
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 869-890 (2024)
Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LESs) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the proper
Externí odkaz:
https://doaj.org/article/7301e19e385047059fe72016b820a8cc
Implications of stochastic effects for primordial black hole production in ultra-slow-roll inflation
Publikováno v:
JCAP05(2022)027
We study the impact of stochastic noise on the generation of primordial black hole (PBH) seeds in ultra-slow-roll (USR) inflation with numerical simulations. We consider the non-linearity of the system by consistently taking into account the noise de
Externí odkaz:
http://arxiv.org/abs/2111.07437
Machine learning (ML) provides us with numerous opportunities, allowing ML systems to adapt to new situations and contexts. At the same time, this adaptability raises uncertainties concerning the run-time product quality or dependability, such as rel
Externí odkaz:
http://arxiv.org/abs/2109.07989
Context: Artificial intelligence (AI) has made its way into everyday activities, particularly through new techniques such as machine learning (ML). These techniques are implementable with little domain knowledge. This, combined with the difficulty of
Externí odkaz:
http://arxiv.org/abs/2107.12190
Autor:
Joutsenlahti, Juha-Pekka, Lehtonen, Timo, Raatikainen, Mikko, Kettunen, Elina, Mikkonen, Tommi
Increasingly common open data and open application programming interfaces (APIs) together with the progress of data science -- such as artificial intelligence (AI) and especially machine learning (ML) -- create opportunities to build novel services b
Externí odkaz:
http://arxiv.org/abs/2103.07290
Autor:
Felfernig, Alexander, Stettinger, Martin, Atas, Müslüm, Samer, Ralph, Nerlich, Jennifer, Scholz, Simon, Tiihonen, Juha, Raatikainen, Mikko
Requirements Engineering in open source projects such as Eclipse faces the challenge of having to prioritize requirements for individual contributors in a more or less unobtrusive fashion. In contrast to conventional industrial software development p
Externí odkaz:
http://arxiv.org/abs/2102.08638