A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.

A collection of resources and papers on Diffusion Models

This repo includes ChatGPT prompt curation to use ChatGPT better.

Acceptance rates for the major AI conferences

10x faster matrix and vector operations

A curated resource list of adversarial attacks and defenses for Windows PE malware detection.

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

深度学习经典、新论文逐段精读

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

links to conference publications in graph-based deep learning

⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~

Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

Code for our DLS'21 paper - BODMAS: An Open Dataset for Learning based Temporal Analysis of PE Malware. BODMAS is short for Blue Hexagon Open Dataset for Malware AnalysiS.

This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

First and Complementary Neighborhood Combination of Adjacency Matrix for Graph Learning

A Direct Neighborhood Combination of the Adjacency Matrix for Graph Learning

Representation Iterative Fusion Based on Heterogeneous Graph Neural Network for Joint Entity and Relation Extraction

Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"

code and trained models for "Attentional Feature Fusion"

A guide on overclocking your NVIDIA GPU in linux

The source codes for Fine-grained Fact Verification with Kernel Graph Attention Network.

A text-to-network representation and semantic parsing toolkit.

Code from the paper: Neurlux: Dynamic Malware Analysis Without Feature Engineering

pefile is a Python module to read and work with PE (Portable Executable) files

Source code of AAAI21-Heterogeneous Graph Structure Learning for Graph Neural Networks