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Convolutional sparse coding implemented on Intel's Loihi 2 hardware

By PulseAugur Editorial · [2 sources] ·

Researchers have developed and benchmarked a convolutional sparse coding implementation using the Locally Competitive Algorithm (LCA) on Intel's Loihi 2 neuromorphic hardware. This work represents the first known implementation and evaluation of convolutional LCA on this platform. The study aims to determine the conditions under which this approach becomes advantageous for sparse inference on neuromorphic systems, positioning it as a benchmark for structured sparse inference. AI

IMPACT Positions convolutional LCA as a benchmark for structured sparse inference on emerging neuromorphic systems.

RANK_REASON Academic paper detailing a new implementation and benchmark of an algorithm on specific hardware.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Geoffrey Kasenbacher, Daniel Ruepp, Gerrit A. Ecke ·

    Convolutional Sparse Coding via the Locally Competitive Algorithm on Loihi 2

    arXiv:2606.08584v1 Announce Type: new Abstract: Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis functions. The Locally Competitive Algorithm (LCA) is particularly attractive in …

  2. arXiv cs.LG TIER_1 English(EN) · Gerrit A. Ecke ·

    Convolutional Sparse Coding via the Locally Competitive Algorithm on Loihi 2

    Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis functions. The Locally Competitive Algorithm (LCA) is particularly attractive in the context of neuromorphic computing because it…

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