1.5k citations
- Technical University of MunichDE11 papers
- Intel (United States)US8 papers
- Technische Universität DarmstadtDE6 papers
- Brookhaven National LaboratoryUS5 papers
- Carnegie Mellon UniversityUS5 papers
- Massachusetts Institute of TechnologyUS5 papers
- ETH ZurichCH4 papers
- Lawrence Berkeley National LaboratoryUS4 papers
- University of North Carolina at Chapel HillUS4 papers
- Deutsches Elektronen-Synchrotron DESYDE3 papers
- GSI Helmholtz Centre for Heavy Ion ResearchDE3 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR2 papers
53 papers
The More the Merrier: Running Multiple Neuromorphic Components On-Chip for Robotic Control
Evan Eames, Priyadarshini Kannan, Ronan Sangouard +9
It has long been realized that neuromorphic hardware offers benefits for the domain of robotics such as low energy, low latency, as well as unique methods of learning. In aiming fo…
A unipolar head gradient for high-field MRI without encoding ambiguity
Markus Weiger, Johan Overweg, Franciszek Hennel +15
Purpose: MRI gradients with a conventional, bipolar design generally face a trade-off between performance, encoding ambiguity, and circumventing the latter by means of RF selectivi…
A Software Platform for Testing Multi-Link Operation in Industrial Wi-Fi Networks
Matteo Rosani, Gianluca Cena, Dave Cavalcanti +3
Multi-Link Operation (MLO) in Wi-Fi 7 is expected to tangibly boost throughput while lowering transmission latency at the same time. This is very relevant in industrial scenarios a…
Graph Reinforcement Learning for Power Grids: A Comprehensive Survey
Mohamed Hassouna, Clara Holzhüter, Pawel Lytaev +3
The increasing share of renewable energy and distributed electricity generation requires the development of deep learning approaches to address the lack of flexibility inherent in…
N-Dimensional Gaussians for Fitting of High Dimensional Functions
Stavros Diolatzis, Tobias Zirr, Alexandr Kuznetsov +2
In the wake of many new ML-inspired approaches for reconstructing and representing high-quality 3D content, recent hybrid and explicitly learned representations exhibit promising p…
The from Lattice QCD: Determining the Finite-volume Spectra
John Bulava, Bárbara Cid-Mora, Andrew D. Hanlon +8
This work presents technical details of determining the finite-volume energy spectra for the scattering amplitude of the coupled-channel from lattice QCD data. The i…