Presents a framework for portable execution of spiking neural networks across von-Neumann HPC and neuromorphic systems via EBRAINS JupyterLab, PyUNICORE, Apptainer containers, and NESTML for model compilation.
The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing
2 Pith papers cite this work, alongside 46 external citations. Polarity classification is still indexing.
2
Pith papers citing it
46
external citations · OpenAlex
verdicts
UNVERDICTED 2representative citing papers
Experts rate AI scenarios as more likely, less risky, more beneficial, and more valuable than the public, applying different weightings to risk versus benefit.
citing papers explorer
-
Unifying von-Neumann HPC and Neuromorphic Acceleration via the EBRAINS Research Infrastructure: A Framework for High-Performance Workflows
Presents a framework for portable execution of spiking neural networks across von-Neumann HPC and neuromorphic systems via EBRAINS JupyterLab, PyUNICORE, Apptainer containers, and NESTML for model compilation.
-
Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI
Experts rate AI scenarios as more likely, less risky, more beneficial, and more valuable than the public, applying different weightings to risk versus benefit.