[NeurIPS 2021 Spotlight] Official code for "Focal Self-attention for Local-Global Interactions in Vision Transformers"
Обновлено 2022-03-27 08:21:56 +03:00
CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped, CVPR 2022
Обновлено 2022-03-18 04:29:20 +03:00
Replication Code for "Self-Supervised Bug Detection and Repair" NeurIPS 2021
Обновлено 2022-03-07 13:03:47 +03:00
Automated auto-assessment with PyBryt via GitHub Actions
Обновлено 2022-03-01 19:34:29 +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
An open source serial monitor cli
Обновлено 2022-02-05 00:34:49 +03:00
A PyTorch Graph Neural Network Library
Обновлено 2022-02-01 20:31:29 +03:00
methods2test is a supervised dataset consisting of Test Cases and their corresponding Focal Methods from a set of Java software repositories
Обновлено 2022-01-20 03:56:30 +03:00
A template for repositories that connect a simulation platform with Microsoft Project Bonsai.
Обновлено 2022-01-20 02:37:12 +03:00
Python for Security is the home of all open source Python projects that can integrate with Microsoft Technologies.
Обновлено 2022-01-11 01:40:23 +03:00
FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.
Обновлено 2022-01-06 19:18:51 +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
MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage/document ranking
Обновлено 2022-01-03 19:13:01 +03:00
Python SDK for the Microsoft Face API, part of Cognitive Services
Обновлено 2021-11-08 16:41:29 +03:00
Обновлено 2021-11-05 02:54:29 +03:00
Ansys Twin Builder connector for Microsoft Bonsai that works with a sample cabin pressure model.
Обновлено 2021-10-26 00:10:47 +03:00
The Microsoft FarmBeats University Community repo, helps educators and students learn about precision agriculture and Internet of Things (IoT) technologies.
Обновлено 2021-10-22 23:21:13 +03:00
Common PyTorch Modules
Обновлено 2021-10-18 13:52:28 +03:00
Обновлено 2021-10-15 05:55:42 +03:00
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This package implements THOR: Transformer with Stochastic Experts.
Обновлено 2021-10-08 00:19:22 +03:00
This is a classification solution accelerator to help you build and deploy a binary classification project.
Обновлено 2021-10-01 18:41:37 +03:00
GitHub Action that imports Databricks notebooks from a local path into the Databricks worspace
Обновлено 2021-10-01 00:29:00 +03:00