Spremljeno u:
Bibliografski detalji
Glavni autor: Muhammad, Akhyar
Format: Recurso digital
Jezik:
Izdano: Zenodo 2026
Teme:
Online pristup:https://doi.org/10.5281/zenodo.20072028
Oznake: Dodaj oznaku
Bez oznaka, Budi prvi tko označuje ovaj zapis!
_version_ 1866902173586030592
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_20072028
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.20072028