Zobrazeno 1 - 10
of 5 927
pro vyhledávání: '"Muhr, A."'
Autor:
Garg, Nikhil, Florini, Davide, Dufour, Patrick, Muhr, Eloir, Faye, Mathieu, Bocquet, Marc, Querlioz, Damien, Beilliard, Yann, Drouin, Dominique, Alibart, Fabien, Portal, Jean-Michel
Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by operating with
Externí odkaz:
http://arxiv.org/abs/2406.19667
Autor:
Schwarting, Julian, Holzberger, Fabian, Muhr, Markus, Renz, Martin, Boeckh-Behrens, Tobias, Wohlmuth, Barbara, Kirschke, Jan
Rupture of intracranial aneurysms results in severe subarachnoidal hemorrhage, which is associated with high morbidity and mortality. Neurointerventional occlusion of the aneurysm through coiling has evolved to a therapeutical standard. The choice of
Externí odkaz:
http://arxiv.org/abs/2403.06889
Endovascular coil embolization is one of the primary treatment techniques for cerebral aneurysms. Although it is a well established and minimally invasive method, it bears the risk of sub-optimal coil placement which can lead to incomplete occlusion
Externí odkaz:
http://arxiv.org/abs/2402.02798
Autor:
Frank, Martin, Holzberger, Fabian, Horvat, Medeea, Kirschke, Jan, Mayr, Matthias, Muhr, Markus, Nebulishvili, Natalia, Popp, Alexander, Schwarting, Julian, Wohlmuth, Barbara
Predicting the long-term success of endovascular interventions in the clinical management of cerebral aneurysms requires detailed insight into the patient-specific physiological conditions. In this work, we not only propose numerical representations
Externí odkaz:
http://arxiv.org/abs/2402.00550
Autor:
Jebali, Fadi, Majumdar, Atreya, Turck, Clément, Harabi, Kamel-Eddine, Faye, Mathieu-Coumba, Muhr, Eloi, Walder, Jean-Pierre, Bilousov, Oleksandr, Michaud, Amadeo, Vianello, Elisa, Hirtzlin, Tifenn, Andrieu, François, Bocquet, Marc, Collin, Stéphane, Querlioz, Damien, Portal, Jean-Michel
Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired with energy harvesters. However, most memristor-based networks rely on
Externí odkaz:
http://arxiv.org/abs/2305.12875
The scores of distance-based outlier detection methods are difficult to interpret, making it challenging to determine a cut-off threshold between normal and outlier data points without additional context. We describe a generic transformation of dista
Externí odkaz:
http://arxiv.org/abs/2305.09446
Autor:
Muhr, Florian, Zaniboni, Lorenzo, Dehkordi, Saeid K., Nieto, Fernando Pedraza, Caire, Giuseppe
In a typical communication system, in order to maintain a desired SNR level, initial beam alignment (BA) must be established prior to data transmission. In a setup where a Base Station (BS) Tx sends data via a digitally modulated waveform, we propose
Externí odkaz:
http://arxiv.org/abs/2304.01848
OutlierDetection.jl is an open-source ecosystem for outlier detection in Julia. It provides a range of high-performance outlier detection algorithms implemented directly in Julia. In contrast to previous packages, our ecosystem enables the developmen
Externí odkaz:
http://arxiv.org/abs/2211.04550
Autor:
Maximilian Muhr, Johannes Stephan, Lena Staiger, Karina Hemmer, Max Schütz, Patricia Heiß, Christian Jandl, Mirza Cokoja, Tim Kratky, Sebastian Günther, Dominik Huber, Samia Kahlal, Jean-Yves Saillard, Olivier Cador, Augusto C. H. Da Silva, Juarez L. F. Da Silva, Janos Mink, Christian Gemel, Roland A. Fischer
Publikováno v:
Communications Chemistry, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract Poorly selective mixed-metal cluster synthesis and separation yield reaction solutions of inseparable intermetalloid cluster mixtures, which are often discarded. High-resolution mass spectrometry, however, can provide precise compositional d
Externí odkaz:
https://doaj.org/article/93716d319cf348ce8922756227af036e
Autor:
Fadi Jebali, Atreya Majumdar, Clément Turck, Kamel-Eddine Harabi, Mathieu-Coumba Faye, Eloi Muhr, Jean-Pierre Walder, Oleksandr Bilousov, Amadéo Michaud, Elisa Vianello, Tifenn Hirtzlin, François Andrieu, Marc Bocquet, Stéphane Collin, Damien Querlioz, Jean-Michel Portal
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired with energy harvesters. However, most memristor-based network
Externí odkaz:
https://doaj.org/article/9069737b51ae4f8bb963f0d34fb0f961