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Zenodo
2026
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| Accesso online: | https://doi.org/10.5281/zenodo.20072074 |
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| _version_ | 1866902173597564928 |
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| author | Muhammad, Akhyar |
| author_facet | Muhammad, Akhyar |
| contents | Oxide-JS (formerly ML-V1) is a high-performance, modular machine learning library for TypeScript, accelerated by optimized Rust kernels via NAPI-RS. This library serves as the successor to the ML-V1 stability research artifacts (v2.3.0) used in the empirical analysis of recurrent neural networks for Indonesian sentiment classification. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20072074 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Oxide-JS: A High-Performance Modular TypeScript ML Library with Rust Kernels Muhammad, Akhyar machine-learning typescript rust napi-rs monorepo neural-networks transformers deep-learning high-performance-computing Oxide-JS (formerly ML-V1) is a high-performance, modular machine learning library for TypeScript, accelerated by optimized Rust kernels via NAPI-RS. This library serves as the successor to the ML-V1 stability research artifacts (v2.3.0) used in the empirical analysis of recurrent neural networks for Indonesian sentiment classification. |
| title | Oxide-JS: A High-Performance Modular TypeScript ML Library with Rust Kernels |
| topic | machine-learning typescript rust napi-rs monorepo neural-networks transformers deep-learning high-performance-computing |
| url | https://doi.org/10.5281/zenodo.20072074 |