{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/exploiting-noise-as-a-resource-for","title":"Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks","arxiv_id":"2305.16044","date":"2023-05-25","proceeding":null,"authors":["Gehua Ma","Rui Yan","Huajin Tang"],"abstract":"$\\textbf{Formal version available at}$ https://cell.com/patterns/fulltext/S2666-3899(23)00200-3 Networks of spiking neurons underpin the extraordinary information-processing capabilities of the brain and have become pillar models in neuromorphic artificial intelligence. Despite extensive research on spiking neural networks (SNNs), most studies are established on deterministic models, overlooking the inherent non-deterministic, noisy nature of neural computations. This study introduces the noisy spiking neural network (NSNN) and the noise-driven learning rule (NDL) by incorporating noisy neuronal dynamics to exploit the computational advantages of noisy neural processing. NSNN provides a theoretical framework that yields scalable, flexible, and reliable computation. We demonstrate that NSNN leads to spiking neural models with competitive performance, improved robustness against challenging perturbations than deterministic SNNs, and better reproducing probabilistic computations in neural coding. This study offers a powerful and easy-to-use tool for machine learning, neuromorphic intelligence practitioners, and computational neuroscience researchers.","url_abs":"https://arxiv.org/abs/2305.16044v6","url_pdf":"https://arxiv.org/pdf/2305.16044v6.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"exploiting-noise-as-a-resource-for","repo_url":"https://github.com/genema/Noisy-Spiking-Neuron-Nets","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[{"method_slug":"adam","method_name":"Adam"},{"method_slug":"sgd","method_name":"SGD"},{"method_slug":"snn","method_name":"SNN"},{"method_slug":"stochastic-gradient-variational-bayes","method_name":"Stochastic Gradient Variational Bayes"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2305.16044","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.16044"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/genema/Noisy-Spiking-Neuron-Nets","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"50b5e780a5cfc0fc","entry":"heaviside","repo":"genema/Noisy-Spiking-Neuron-Nets","repo_kind":"official","path":"models/NILIF.py","file_url":"https://github.com/genema/Noisy-Spiking-Neuron-Nets/blob/HEAD/models/NILIF.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"LGPL-2.1","inline_ok":false,"mcp_get_code":{"code_sha256":"50b5e780a5cfc0fc"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}