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Neuroevolution is one of the methodologies that can be used for learning optimal architecture during training.
Lof: Identifying density-based local outliers
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, and Jörg Sander · 2000
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Evolving neural networks through augmenting topologies
Kenneth O. Stanley and Risto Miikkulainen · 2002
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Fast outlier detection in high dimensional spaces
Fabrizio Angiulli and Clara Pizzuti · 2002
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Time-series novelty detection using one-class support vector machines
J. Ma and S. Perkins · 2003
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Model-based fault detection and diagnosis - status and applications
Rolf Isermann · 2004
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Isolation forest
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou · 2008
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A hypercube-based indirect encoding for evolving large-scale neural networks
Kenneth O. Stanley, David Ambrosio, and Jason Gauci · 2009
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Anomaly detection: A survey
V. Chandola, A. Banerjee, and V. Kumar · 2009
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Rectifier nonlinearities improve neural network acoustic models
Andrew L. Maas, Awni Y. Hannun, and Andrew Y. Ng · 2013
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Generalized denoising auto-encoders as generative models
Y. Bengio, G. Alain L. Yao, and P. Vincent · 2013
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Algorithmica
Analysis of agglomerative clustering · 2014
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A. Makhzani, J. Shlens, N. Jaitly, I. Goodfellow, and B. Frey · 2015
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Lstm-based encoder-decoder for multi-sensor anomaly detection
P. Malhotra, A. Ramakrishnan, G. Anand, L. Vig, P. Agarwal, and G. Shroff · 2016
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Spectrum-diverse neuroevolution with unified neural models
Danilo Vasconcellos Vargas and Junichi Murata · 2016
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Swat: a water treatment testbed for research and training on ics security
Aditya P. Mathur and Nils Ole Tippenhauer · 2016
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R. Miikkulainen, J. Liang, E. Meyerson, A. Rawal, D. Fink, O. Francon, B. Raju, H. Shahrzad, A. Navruzyan, N. Duffy, and B. Hodjat · 2017
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Neuroevolution of autoencoders by genetic algorithm
Hidehiko Okada · 2017
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Wadi: a water distribution testbed for research in the design of secure cyber physical systems
Chuadhry Ahmed, Venkata Palleti, and Aditya Mathur · 2017
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Evolving deep convolutional neural networks for image classification
Yanan Sun, Bing Xue, Mengjie Zhang, and Gary G. Yen · 2017
Cited alongside, same era.
A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoencoder
Daehyung Park, Yuuna Hoshi, and Charles C. Kemp · 2018
Cited alongside, same era.
Detecting spacecraft anomalies using lstms and nonparametric dynamic thresholding
K. Hundman, V. Constantinou, C. Laporte, I. Colwell, and T. Soderstrom · 2018
Cited alongside, same era.
An empirical evaluation of generic convolutional and recurrent networks for sequence modeling, 2018
Shaojie Bai, J. Zico Kolter, and Vladlen Koltun · 2018
Cited alongside, same era.
Deep autoencoding gaussian mixture model for unsupervised anomaly detection
B. Zong, Q. Song, M. R. Min, W. Cheng, C. Lumezanu, D. Cho, , and H. Chen · 2018
Cited alongside, same era.
Robust anomaly detection for multivariate time series through stochastic recurrent neural network
Y. Su, Y. Zhao, C. Niu, R. Liu, W. Sun, and D. Pei · 2019
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Mad-gan: Multivariate anomaly detection for time series data with generative adversarial networks
Dan Li, Dacheng Chen, Baihong Jin, Lei Shi, Jonathan Goh, and See-Kiong Ng · 2019
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Outlier detection for time series with recurrent autoencoder ensembles
T. Kieu, B. Yang, C. Guo, and C. S. Jensen · 2019
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Usad: Unsupervised anomaly detection on multivariate time series
Julien Audibert, Pietro Michiardi, Frédéric Guyard, Sébastien Marti, and Maria A. Zuluaga · 2020
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A review on outlier/anomaly detection in time series data
A. Blazquez-Garc´ıa, A. Conde, U. Mori, and J. A. Lozano · 2020
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A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoencoder
D. Park, Y. Hoshi, and C. C. Kemp · 2018
Cited alongside, same era.
Self-organizing neuroevolution for solving carpool service problem with dynamic capacity to alternate matches
Ming-Kai Jiau and Shih-Chia Huang · 2018
Cited alongside, same era.
Deep autoencoding gaussian mixture model for unsupervised anomaly detection
Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, C. Lumezanu, Dae ki Cho, and H. Chen · 2018
Cited alongside, same era.
Kitsune: An ensemble of autoencoders for online network intrusion detection
Yisroel Mirsky, Tomer Doitshman, Y. Elovici, and Asaf Shabtai · 2018
Cited alongside, same era.
An empirical evaluation of generic convolutional and recurrent networks for sequence modeling
S. Bai, J. Z. Kolter, and V. Koltun · 2018
Cited alongside, same era.
Threaded ensembles of autoencoders for stream learning
Yue Dong and Nathalie Japkowicz · 2018
Cited alongside, same era.
Deep learning for anomaly detection: A survey
R. Chalapathy and S. Chawla · 2019
Cited alongside, same era.
P. Mooney E. Galvan · 2020
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Up or down? adaptive rounding for post-training quantization
Markus Nagel, Rana A. Amjad, Mart van Baalen, Christos Louizos, and Tijmen Blankevoort · 2020
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Anomaly detection using deep autoencoders for in-situ wastewater systems monitoring data, 2020
Stefania Russo, Andy Disch, Frank Blumensaat, and Kris Villez · 2020
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A malware detection approach using malware images and autoencoders
Xiang Jin, Xiaofei Xing, Haroon Elahi, Guojun Wang, and Hai Jiang · 2020
Later among the works it cites.
Ensemble neuroevolution-based approach for multivariate time series anomaly detection
Kamil Faber, Marcin Pietron, and Dominik Zurek · 2021
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Graph neural network-based anomaly detection in multivariate time series, 2021
Ailin Deng and Bryan Hooi · 2021
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An evaluation of anomaly detection and diagnosis in multivariate time series
Astha Garg, Wenyu Zhang, Jules Samaran, Ramasamy Savitha, and Chuan-Sheng Foo · 2021
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Moncae: Multi-objective neuroevolution of convolutional autoencoders
Daniel Dimanov, Emili Balaguer-Ballester, Colin Singleton, and Shahin Rostami · 2021
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Topicbert: A topic-enhanced neural language model fine-tuned for sentiment classification
Yuxiang Zhou, Lejian Liao, Yang Gao, Rui Wang, and Heyan Huang · 2021
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Rollback ensemble with multiple local minima in fine-tuning deep learning networks
Youngmin Ro, Jongwon Choi, Byeongho Heo, and Jin Young Choi · 2021
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Scenenet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search
A. Ma, Y. Wan, Y. Zhong, and J. Wang · 2021
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Snippet policy network v2: Knee-guided neuroevolution for multi-lead ecg early classification
Yu Huang, Gary Yen, and Vincent Tseng · 2022
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