业务流程设计器（OFD）是一个图形用户界面应用程序，它支持将知识图作为自助服务工具。它帮助用户创建特定于项目域的流程图，促进直观和高效的数据编排。
The Orchestration Flow Designer (OFD) is a graphical user interface application that enables knowledge graphs as a self-service tool. It assists users in creating project domain-specific flow graphs, facilitating intuitive and efficient data orchestration. (2024-05-10, TypeScript, 0KB, 下载0次)
物理信息神经网络（PINN）使用通用函数逼近器将PDE描述的物理定律的知识集成到学习过程中，解决生物和工程系统中的数据稀缺问题。
Physics-informed neural networks(PINN) use universal function approximators to integrate knowledge of physical laws described by PDEs into the learning process, addressing data scarcity in biological and engineering systems. (2024-05-07, Jupyter Notebook, 0KB, 下载0次)
这是一个用于注册的存储库，它将一些区域嵌入到HAVANA中，HAVANA是一种图形神经网络，对分类器的语义兴趣点负责。
This is a repository for registry the advanced of including some region embeddings into HAVANA, a graph neural network responsable to classifier semantically points of interests. (2024-03-24, Makefile, 0KB, 下载0次)
GECCO是一种基于单个MLP和图卷积层的轻量级图像分类器。我们发现，与其他最先进的模型相比，我们的模型可以实现高达16倍的延迟。我们模型的论文可以在https:arxiv.org abs 2402.00564上找到
GECCO is a lightweight image classifier based on single MLP and graph convolutional layers. We find that our model can achieve up to 16x better latency than other state-of-the-art models. The paper for our model can be found at https: arxiv.org abs 2402.00564 (2024-02-27, Python, 0KB, 下载0次)
从Neo4J数据库生成GraphQL模式和解析器，因此您不必手动创建模式。还可以获得...
Generated GraphQL schemas and resolvers from Neo4J Database so you don t have to manually created schema. Also get anything from Database just by passing command in request. (2018-06-04, JavaScript, 58KB, 下载0次)
Pytorch和Pytorch Geometric中用于图神经网络的多掩码聚合器的正式实现
Official Implementation of Multi-Masked Aggregators for Graph Neural Networks in Pytorch and PyTorch Geometric (2023-03-24, Python, 5291KB, 下载0次)
一个用于创建图神经网络的模型构建器助手，类似于[https://arxiv.org abs 1806.0...]（https://arxiv.org abs 1806.01261）中描述的网络
A model builder helper for creating graph neural networks akin to the ones described in <https://arxiv.org/abs/1806.01261> and <https://ieeexplore.ieee.org/document/4700287> (2019-04-18, Python, 17KB, 下载0次)
这是IJCAI 2022论文的实现演示[使用...消除深度神经网络的后门触发器...
This is an implementation demo of the IJCAI 2022 paper [Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation](<https://arxiv.org/abs/2204.09975>) in PyTorch. (2022-07-04, Python, 17666KB, 下载0次)