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Anomaly Detection, Anomaly Segmentation, Novelty Detection, Out-of-Distribution Detection

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TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

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Datasets

Greatest papers with code

Temporal Cycle-Consistency Learning

CVPR 2019 google-research/google-research

We introduce a self-supervised representation learning method based on the task of temporal alignment between videos.

ANOMALY DETECTION REPRESENTATION LEARNING SELF-SUPERVISED LEARNING VIDEO ALIGNMENT

PyOD: A Python Toolbox for Scalable Outlier Detection

6 Jan 2019yzhao062/pyod

PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data.

Ranked #3 on on

ANOMALY DETECTION OUTLIER ENSEMBLES

Learning Retrospective Knowledge with Reverse Reinforcement Learning

NeurIPS 2020 ShangtongZhang/DeepRL

We present a Reverse Reinforcement Learning (Reverse RL) approach for representing retrospective knowledge.

ANOMALY DETECTION REPRESENTATION LEARNING

Large-Scale Intelligent Microservices

17 Sep 2020Azure/mmlspark

Deploying Machine Learning (ML) algorithms within databases is a challenge due to the varied computational footprints of modern ML algorithms and the myriad of database technologies each with its own restrictive syntax.

ANOMALY DETECTION

DeepWalk: Online Learning of Social Representations

26 Mar 2014williamleif/GraphSAGE

We present DeepWalk, a novel approach for learning latent representations of vertices in a network.

ANOMALY DETECTION LANGUAGE MODELLING NODE CLASSIFICATION

GluonTS: Probabilistic Time Series Models in Python

12 Jun 2019awslabs/gluon-ts

We introduce Gluon Time Series (GluonTS, available at https://gluon-ts. mxnet. io), a library for deep-learning-based time series modeling.

ANOMALY DETECTION TIME SERIES TIME SERIES FORECASTING TIME SERIES PREDICTION

Unsupervised real-time anomaly detection for streaming data

Neurocomputing 2017 numenta/NAB

We present results and analysis for a wide range of algorithms on this benchmark, and discuss future challenges for the emerging field of streaming analytics.

ANOMALY DETECTION TIME SERIES

Real-Time Anomaly Detection for Streaming Analytics

8 Jul 2016numenta/NAB

Much of the worlds data is streaming, time-series data, where anomalies give significant information in critical situations.

ANOMALY DETECTION TIME SERIES

Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection

25 Jan 2016numenta/NAB

We present a novel algorithm for anomaly detection on very large datasets and data streams.

ANOMALY DETECTION INCREMENTAL LEARNING

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

12 Oct 2015numenta/NAB

Here we propose the Numenta Anomaly Benchmark (NAB), which attempts to provide a controlled and repeatable environment of open-source tools to test and measure anomaly detection algorithms on streaming data.

ANOMALY DETECTION TIME SERIES