most citedHigher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AR2026

A Unified Interconnection Network for Chiplet-Based Scaling of the BrainScaleS Neuromorphic System

Robin Heinemann, Johannes Schemmel

The BrainScaleS-2 (BSS-2) neuromorphic architecture combines analog emulation of spiking neural network (SNN) primitives with tightly coupled ADCs and digital processing units. The…

cs.NE2026

Amortized Inference of Neuron Parameters on Analog Neuromorphic Hardware

Jakob Kaiser, Eric Müller, Johannes Schemmel

Our work utilized a non-sequential simulation-based inference algorithm to provide an amortized neural density estimator, which approximates the posterior distribution for seven pa…

cs.AR2025

The BrainScaleS-2 multi-chip system: Interconnecting continuous-time neuromorphic compute substrates

Joscha Ilmberger, Johannes Schemmel

The BrainScaleS-2 SoC integrates analog neuron and synapse circuits with digital periphery, including two CPUs with SIMD extensions. Each ASIC is connected to a Node-FPGA, providin…

cs.NE2025★ 1 cited

Higher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability

Faiek Ahsan, Saptarshi Maiti, Zihao Chen +8

We report a higher-order neuromorphic Ising machine that exhibits superior scalability compared to architectures based on quadratization, while also achieving state-of-the-art qual…

cs.AR2025

Sustainable operation of research infrastructure for novel computing

Yannik Stradmann, Joscha Ilmberger, Eric Müller +1

Novel compute systems are an emerging research topic, aiming towards building next-generation compute platforms. For these systems to thrive, they need to be provided as research i…