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With Moore's law coming to an end, increasingly more hope is being put in specialized hardware implemented on reconfigurable architectures such as Field-Programmable Gate Arrays (FPGAs). Yet, it is often neglected that these architectures themselves experi ...
This article focuses on spectral methods for recovering communities in temporal networks. In the case of fixed communities, spectral clustering on the simple time-aggregated graph (i.e., the weighted graph formed by the sum of the interactions over all tem ...
The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators.Specialized hardware has already redefined ...
Factored form is a powerful multi-level representation of a Boolean function that readily translates into an implementation of the function in CMOS technology. In particular, the number of literals in a factored form correlates strongly with the number of ...
Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...
The engineering of tin halide perovskites has led to the development of p-type transistors with field-effect mobilities of over 70 cm2 V-1 s-1. However, due to their background hole doping, these perovskites are not suitable for n-type transistors. Ambipol ...
The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...
Graph neural networks (GNNs) have demonstrated promising performance across various chemistry-related tasks. However, conventional graphs only model the pairwise connectivity in molecules, failing to adequately represent higher order connections, such as m ...
In this master thesis, multi-agent reinforcement learning is used to teach robots to build a self-supporting structure connecting two points. To accomplish this task, a physics simulator is first designed using linear programming. Then, the task of buildin ...
Organic electrochemical transistors (OECTs) have gained enormous attention due to their potential for bioelectronics and neuromorphic computing. However, their implementation into real-world applications is still impeded by a lack of understanding of the c ...
