About
Anomaly Detection, Anomaly Segmentation, Novelty Detection, Out-of-Distribution Detection
Benchmarks
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Subtasks
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.
Ranked #1 on
Video Alignment
on UPenn Action
ANOMALY DETECTION REPRESENTATION LEARNING SELF-SUPERVISED LEARNING VIDEO ALIGNMENT
PyOD: A Python Toolbox for Scalable Outlier Detection
• yzhao062/pyod
•
PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data.
Ranked #3 on
on
Learning Retrospective Knowledge with Reverse Reinforcement Learning
NeurIPS 2020
• ShangtongZhang/DeepRL
• 
We present a Reverse Reinforcement Learning (Reverse RL) approach for representing retrospective knowledge.
Large-Scale Intelligent Microservices
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.
DeepWalk: Online Learning of Social Representations
We present DeepWalk, a novel approach for learning latent representations of vertices in a network.
Ranked #3 on
Node Classification
on Wikipedia
GluonTS: Probabilistic Time Series Models in Python
• awslabs/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
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.
Ranked #1 on
Anomaly Detection
on Numenta Anomaly Benchmark
Real-Time Anomaly Detection for Streaming Analytics
Much of the worlds data is streaming, time-series data, where anomalies give significant information in critical situations.
Ranked #7 on
Anomaly Detection
on Numenta Anomaly Benchmark
Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection
We present a novel algorithm for anomaly detection on very large datasets and data streams.
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark
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.
Ranked #3 on
Anomaly Detection
on Numenta Anomaly Benchmark