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Deep Generative Modeling in Constraint Discovery and Anomaly Detection

https://doi.org/10.2139/ssrn.4790043
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-59050-9_12openalex-extracted
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
inferredcites →https://doi.org/10.1007/s10115-003-0132-7openalex-extracted
Using artificial anomalies to detect unknown and known network intrusions
inferredcites →https://doi.org/10.1007/s10115-023-01929-zopenalex-extracted
Distributional constraint discovery for intelligent auditing
inferredcites →https://doi.org/10.1016/j.future.2015.01.001openalex-extracted
A survey of anomaly detection techniques in financial domain
inferredcites →https://doi.org/10.1038/s41467-019-13055-yopenalex-extracted
Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets
inferredcites →https://doi.org/10.1093/comjnl/42.2.100openalex-extracted
Tane: An Efficient Algorithm for Discovering Functional and Approximate Dependencies
inferredcites →https://doi.org/10.1109/icassp.2011.5947611openalex-extracted
Extensions of recurrent neural network language model
inferredcites →https://doi.org/10.1109/icde48307.2020.00087openalex-extracted
Online Anomalous Trajectory Detection with Deep Generative Sequence Modeling
inferredcites →https://doi.org/10.1109/icde51399.2021.00011openalex-extracted
DBSCOUT: A Density-based Method for Scalable Outlier Detection in Very Large Datasets
inferredcites →https://doi.org/10.1109/icde51399.2021.00049openalex-extracted
Latent Low-rank Graph Learning for Multimodal Clustering
inferredcites →https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom57177.2022.00017openalex-extracted
IceBerg: Deep Generative Modeling for Constraint Discovery and Anomaly Detection
inferredcites →https://doi.org/10.1109/tkde.2010.154openalex-extracted
Discovering Conditional Functional Dependencies
inferredcites →https://doi.org/10.1109/tkde.2019.2905606openalex-extracted
Generative Adversarial Active Learning for Unsupervised Outlier Detection
inferredcites →https://doi.org/10.1109/tkde.2019.2954317openalex-extracted
Clustering With Outlier Removal
inferredcites →https://doi.org/10.1137/1.9781611972795.13openalex-extracted
Outlier Detection with Globally Optimal Exemplar-Based GMM
inferredcites →https://doi.org/10.1145/1366102.1366103openalex-extracted
Conditional functional dependencies for capturing data inconsistencies
inferredcites →https://doi.org/10.1145/3318464.3384683openalex-extracted
AUDITOR: A System Designed for Automatic Discovery of Complex Integrity Constraints in Relational Databases
inferredcites →https://doi.org/10.1145/3318464.3389749openalex-extracted
A Statistical Perspective on Discovering Functional Dependencies in Noisy Data
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-extracted
Long Short-Term Memory
inferredcites →https://doi.org/10.1371/journal.pone.0152173openalex-extracted
A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data
inferredcites →https://doi.org/10.14778/3157794.3157800openalex-extracted
Efficient denial constraint discovery with hydra
inferredcites →https://doi.org/10.14778/3368289.3368293openalex-extracted
Discovery of approximate (and exact) denial constraints
inferredcites →https://doi.org/10.14778/3377369.3377377openalex-extracted
Pattern functional dependencies for data cleaning
inferredcites →https://doi.org/10.1631/jzus.a2200156openalex-extracted
Complex integrity constraint discovery: measuring trust in modern intelligent railroad systems
inferredcites →https://doi.org/10.48550/arxiv.1312.6114openalex-extracted
Auto-Encoding Variational Bayes
inferredcites →https://doi.org/10.48550/arxiv.1412.3555openalex-extracted
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1802.00187openalex-extracted
Clustering and Unsupervised Anomaly Detection with L2 Normalized Deep Auto-Encoder Representations
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