Stars
Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。
Paper list for industrial image anomaly synthesis methods.
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Ruleset covering algorithms for transparent machine learning
MTAD: Tools and Benchmark for Multivariate Time Series Anomaly Detection
BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection (WWW23)
The PyTorch implementation for "BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection"
Public datasets for time series anomaly detection
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We…
PyTorch implementation for Dual Contrastive Prediction for Incomplete Multi-view Representation Learning (TPAMI'22)
code and data for the time series analysis vids on my YouTube channel
Slides to accompany Forecasting: Principles and Practice, 3rd edition
Pytorch implementation of "Exploring Interpretable LSTM Neural Networks over Multi-Variable Data" https://arxiv.org/pdf/1905.12034.pdf
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Project for <SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation> (ECCV 2022)
[CVPR 2023] Unofficial re-implementation of "WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation".
ICLR21 Tent: Fully Test-Time Adaptation by Entropy Minimization
Pytorch implementation of DAPrompt: https://arxiv.org/abs/2202.06687
A curated list of awesome papers on dataset distillation and related applications.
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Zero-Shot Learning part)