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eNSEMPLE. It is an interdisciplinary project at the interface between Statistical Physics, Data Science, Network Science, Computer Science and Sociology, and will involve collaborations with researchers from
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for quantized and pruned neural networks, creation of quantized and pruned demonstration models, reproduction of state of the art, experiments in heterogeneous quantization Depending on expertise
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architectures, with a strong focus on spiking neural networks (SNNs). 1 Abstract The increasing availability of spatio-temporal data has enabled significant advances in perception and pattern recognition systems
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, which aims to develop novel solutions for the detection and reaction to cyber attacks, we are recruiting a Post-doctoral fellow within our Network Systems, Cybersecurity and Digital Law (SRCD) department
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developed for centralized settings, they do not account for the distributed nature of critical infrastructures, nor the network induced imperfections like variable sampling periods and communication delays
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of variable distributions [13,14]. Graphic neural networks (GNNs) are new inference methods developed in recent years and are attracting increasing attention due to their efficiency and ability in solving
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 1 month ago
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-of-the-art approaches have been developed for linear systems in centralized settings; they do not consider the distributed nature of the CIs and the network induced imperfections like variable sampling periods
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-Curie doctoral network Recruited researchers will be part of the EURECA doctoral programme, which offers: - A thorough scientific education within a structured doctoral training programme. - The
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Infrastructure? No Offer Description This project is part of the European ERC Synergy project Karst https://erc-karst.eu/ , which aims to develop a predictive flow model for an entire karst network. We will