Tool for generating dom related TypeScript and JavaScript library files
Обновлено 2024-11-21 01:32:46 +03:00
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
machine-learning
deep-learning
data-science
python
automated-machine-learning
natural-language-processing
hyperparameter-optimization
automl
jupyter-notebook
timeseries-forecasting
tuning
classification
finetuning
hyperparam
natural-language-generation
random-forest
regression
scikit-learn
tabular-data
Обновлено 2024-11-20 10:51:18 +03:00
ASP.NET Boilerplate - Web Application Framework
dotnet
csharp
dotnet-core
c-sharp
aspnetcore
architecture
aspnet-core
best-practices
aspnet
framework
domain-driven-design
multi-tenancy
abp
nlayer-architecture
Обновлено 2024-11-20 09:13:31 +03:00
A behavioral analytics library that uses dom mutations and user interactions to generate aggregated insights.
Обновлено 2024-11-19 01:50:34 +03:00
📸🔀☁️ Random Nextcloud log in background from Unsplash
Обновлено 2024-11-18 04:57:04 +03:00
Perception toolkit for sim2real training and validation in Unity
machine-learning
computer-vision
deep-learning
detection
domain-randomization
object-detection
perception
pose-estimation
segmentation
synthetic-dataset-generation
Обновлено 2024-11-08 22:38:42 +03:00
👼 The ultimate angle brackets parser library parsing HTML5, MathML, SVG and CSS to construct a DOM based on the official W3C specifications.
Обновлено 2024-10-01 17:29:41 +03:00
rewrite constructor arguments, call DOMPurify, profit
Обновлено 2024-09-24 23:13:14 +03:00
👼 Extends AngleSharp with a .NET-based JavaScript engine.
Обновлено 2024-07-24 14:14:40 +03:00
Fork of the ms svg library
Обновлено 2024-07-17 20:42:39 +03:00
The AAS WorldWide Telescope Do-It-Yourself Planetarium Dome Guide
Обновлено 2024-06-11 18:12:21 +03:00
👼 Adds XPath support to AngleSharp as an alternative to CSS selectors.
Обновлено 2024-04-01 19:14:11 +03:00
👼 Library to add XML and DTD parsing capabilities to AngleSharp.
Обновлено 2024-02-25 18:07:40 +03:00
TypeScript library for implementing Domain-Driven Design in web apps
Обновлено 2023-10-25 00:23:54 +03:00
Style Normalization and Restitution for Domain Generalization and Adaptation
Обновлено 2023-10-04 00:19:13 +03:00
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
machine-learning
artificial-intelligence
causality
domain-generalization
privacy-preserving-machine-learning
Обновлено 2023-10-03 07:31:52 +03:00
A categorical heat-map of a metric over the time domain
Обновлено 2023-10-03 01:39:34 +03:00
Quality domain agnostic regular expression pattern matcher that persists results to SARIF
Обновлено 2023-08-29 02:49:35 +03:00
The AAS WorldWide Telescope multi-channel dome setup guide
Обновлено 2023-08-04 00:17:05 +03:00
An algorithm for cross-domain NL2SQL
Обновлено 2023-07-22 23:20:17 +03:00
Sample code for SatchelJS
Обновлено 2023-07-11 21:09:11 +03:00
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021)
deep-learning
computer-vision
neural-network
semantic-segmentation
semi-supervised-learning
domain-adaptation
pseudo-label
Обновлено 2023-07-07 00:28:52 +03:00
SynthDet - An end-to-end object detection pipeline using synthetic data
machine-learning
deep-learning
computer-vision
pose-estimation
synthetic-data
synthetic-dataset-generation
detection
domain-randomization
object-detection
synthetic-dataset
Обновлено 2023-07-05 23:50:31 +03:00
Demonstrates a minimally viable domain controller configuration script compatible with Azure Automation Desired State Configuration service.
Обновлено 2023-06-27 16:03:53 +03:00
A tightly optimized representation of ordered, long-living, often-modified, predicate-filtered lists random-accessible by value and index. (Java)
Обновлено 2023-06-12 23:27:40 +03:00
Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural model with key phrase extraction on open domains we have created OpenKP: a dataset of over 150,000 documents with the most relevant keyphrases generated by expert annotation.
Обновлено 2023-06-12 21:21:58 +03:00
Official Implementation of "A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining""
Обновлено 2023-06-12 21:16:08 +03:00
Samples to use the Microsoft.SystemForCrossDomainIdentityManagement libraries with BYOA for provisioning scenarios
Обновлено 2023-01-24 20:24:29 +03:00