Mozilla's Localization Platform
Обновлено 2024-09-17 22:26:52 +03:00
Provides a set of useful tools, utilities, reusable components, and React hooks that are designed to capture common components and utilities common among Essex Alpha team projects.
Обновлено 2024-09-16 20:26:45 +03:00
Official repository for our NeurIPS 2021 paper "Unadversarial Examples: Designing Objects for Robust Vision"
Обновлено 2024-07-25 14:04:47 +03:00
This is a fun, new monospaced font that includes programming ligatures and is designed to enhance the modern look and feel of the Windows Terminal.
Обновлено 2024-07-06 05:15:34 +03:00
We design an effective Relation-Aware Global Attention (RGA) module for CNNs to globally infer the attention.
Обновлено 2023-06-12 21:55:25 +03:00
BANG is a new pretraining model to Bridge the gap between Autoregressive (AR) and Non-autoregressive (NAR) Generation. AR and NAR generation can be uniformly regarded as to what extent previous tokens can be attended, and BANG bridges AR and NAR generation by designing a novel model structure for large-scale pretraining. The pretrained BANG model can simultaneously support AR, NAR and semi-NAR generation to meet different requirements.
Обновлено 2022-02-06 23:57:17 +03:00
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
Обновлено 2022-01-06 09:18:00 +03:00