Zobrazeno 1 - 10
of 8 307
pro vyhledávání: '"A. Flouris"'
The autoencoder model typically uses an encoder to map data to a lower dimensional latent space and a decoder to reconstruct it. However, relying on an encoder for inversion can lead to suboptimal representations, particularly limiting in physical sc
Externí odkaz:
http://arxiv.org/abs/2412.00864
Autor:
Wang, Yanke, Lee, Yolanne Y. R., Dolfini, Aurelio, Reischl, Markus, Konukoglu, Ender, Flouris, Kyriakos
Publikováno v:
MICCAI Workshop on Deep Generative Models, 2024
Lumbar spine problems are ubiquitous, motivating research into targeted imaging for treatment planning and guided interventions. While high resolution and high contrast CT has been the modality of choice, MRI can capture both bone and soft tissue wit
Externí odkaz:
http://arxiv.org/abs/2412.00511
We study interactions between agents in multi-agent systems, in which the agents are misinformed with regards to the game that they play, essentially having a subjective and incorrect understanding of the setting, without being aware of it. For that,
Externí odkaz:
http://arxiv.org/abs/2409.04854
Quantum machine learning (QML) is a rapidly expanding field that merges the principles of quantum computing with the techniques of machine learning. One of the powerful mathematical frameworks in this domain is tensor networks. These networks are use
Externí odkaz:
http://arxiv.org/abs/2406.17441
Autor:
Flouris, Kyriakos, Konukoglu, Ender
Manifold learning flows are a class of generative modelling techniques that assume a low-dimensional manifold description of the data. The embedding of such a manifold into the high-dimensional space of the data is achieved via learnable invertible t
Externí odkaz:
http://arxiv.org/abs/2310.12743
Autor:
Ploumidis, Manolis, Chaix, Fabien, Chrysos, Nikolaos, Assiminakis, Marios, Flouris, Vassilis, Kallimanis, Nikolaos, Kossifidis, Nikolaos, Nikoloudakis, Michael, Petrakis, Polydoros, Dimou, Nikolaos, Gianioudis, Michael, Ieronymakis, George, Ioannou, Aggelos, Kalokerinos, George, Xirouchakis, Pantelis, Ailamakis, George, Damianakis, Astrinos, Ligerakis, Michael, Makris, Ioannis, Vavouris, Theocharis, Katevenis, Manolis, Papaefstathiou, Vassilis, Marazakis, Manolis, Mavroidis, Iakovos
We present and evaluate the ExaNeSt Prototype, a liquid-cooled rack prototype consisting of 256 Xilinx ZU9EG MPSoCs, 4 TBytes of DRAM, 16 TBytes of SSD, and configurable interconnection 10-Gbps hardware. We developed this testbed in 2016-2019 to vali
Externí odkaz:
http://arxiv.org/abs/2307.09371
We consider misinformation games, i.e., multi-agent interactions where the players are misinformed with regards to the game that they play, essentially having an \emph{incorrect} understanding of the game setting, without being aware of their misinfo
Externí odkaz:
http://arxiv.org/abs/2307.01516
Variational autoencoders (VAEs) are powerful generative modelling methods, however they suffer from blurry generated samples and reconstructions compared to the images they have been trained on. Significant research effort has been spent to increase
Externí odkaz:
http://arxiv.org/abs/2304.05939
Autor:
Harun Torlakcik, Semih Sevim, Pedro Alves, Michael Mattmann, Joaquim Llacer‐Wintle, Maria Pinto, Rosa Moreira, Andreas D. Flouris, Fabian C. Landers, Xiang‐Zhong Chen, Josep Puigmartí‐Luis, Quentin Boehler, Tiago Sotto Mayor, Minsoo Kim, Bradley J. Nelson, Salvador Pané
Publikováno v:
Advanced Science, Vol 11, Iss 38, Pp n/a-n/a (2024)
Abstract The initial delivery of small‐scale magnetic devices such as microrobots is a key, but often overlooked, aspect for their use in clinical applications. The deployment of these devices within the dynamic environment of the human body presen
Externí odkaz:
https://doaj.org/article/5578f56a5ed1492b879832c051c4cd09
Autor:
Flouris, Kyriakos, Jimenez-del-Toro, Oscar, Aberle, Christoph, Bach, Michael, Schaer, Roger, Obmann, Markus, Stieltjes, Bram, Mueller, Henning, Depeursinge, Adrien, Konukoglu, Ender
Publikováno v:
Scientific Reports volume 12, Article number: 4732 (2022)
Medical imaging quantitative features had once disputable usefulness in clinical studies. Nowadays, advancements in analysis techniques, for instance through machine learning, have enabled quantitative features to be progressively useful in diagnosis
Externí odkaz:
http://arxiv.org/abs/2210.02759