308 Open source projects that are alternatives of or similar to Meta-GDN_AnomalyDetection

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

A quick and dirty vehicle speed detector using video + anomaly detection

Tutorials for Machine Learning on Graphs

Probabilistic Type Inference using Graph Neural Networks

Awesome Graph Self-Supervised Learning

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

Graph-based machine learning for chemical property prediction

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

a deep recurrent model for exchangeable data

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

ICML'2022: Black-Box Tuning for Language-Model-as-a-Service

Sherlock is an anomaly detection service built on top of Druid

A curated list of awesome graph & self-supervised-learning-based recommendation.

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

https://events.kaspersky.com/hackathon/

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

A spherical CNN for weather forecasting

The Combined Anomalous Object Segmentation (CAOS) Benchmark

Reimplementation of Graph Embedding methods by Pytorch.

[ICCV'21] Official PyTorch implementation of Relational Embedding for Few-Shot Classification

An index of recommendation algorithms that are based on Graph Neural Networks.

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

AAAI'21: Data Augmentation for Graph Neural Networks

MemStream: Memory-Based Streaming Anomaly Detection

A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification

Representation Learning on Graphs with Jumping Knowledge Networks

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

Representing Long-Range Context for Graph Neural Networks with Global Attention

Pytorch differentiable molecular dynamics

Implementation of feature engineering from Feature engineering strategies for credit card fraud

source code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)

Mean-Shifted Contrastive Loss for Anomaly Detection

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

基于智能计算框架nupic的异常检测restful Api.

Geometric Deep Learning for Flux

Code and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"

Message Passing Neural Networks for Simplicial and Cell Complexes

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

Locally Private Graph Neural Networks (ACM CCS 2021)

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Matching Networks for one-shot learning in tensorflow (NIPS'16)

FSL-Mate: A collection of resources for few-shot learning (FSL).