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In this paper, we present a memory-augmented algorithm for anomaly detection.
On estimation of a probability density function and mode
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Support vector method for novelty detection
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Isolation forest
Liu, F. T., Ting, K. M., and Zhou, Z.-H · 2008
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Visualizing data using t-sne
Maaten, L. v. d. and Hinton, G · 2008
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Anomaly-based network intrusion detection: Techniques, systems and challenges
Garcia-Teodoro, P., Diaz-Verdejo, J., Maciá-Fernández, G., and Vázquez, E · 2009
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A comprehensive survey of data mining-based fraud detection research
Phua, C., Lee, V., Smith, K., and Gayler, R · 2010
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Graves, A., Wayne, G., and Danihelka, I · 2014
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Variational autoencoder based anomaly detection using reconstruction probability
An, J. and Cho, S · 2015
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Deep learning
LeCun, Y., Bengio, Y., and Hinton, G · 2015
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Winner-take-all autoencoders
Makhzani, A. and Frey, B. J · 2015
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., and Abbeel, P · 2016
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Donahue, J., Krähenbühl, P., and Darrell, T · 2016
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Adversarially learned inference
Dumoulin, V., Belghazi, I., Poole, B., Mastropietro, O., Lamb, A., Arjovsky, M., and Courville, A · 2016
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High-dimensional and large-scale anomaly detection using a linear one-class svm with deep learning
Erfani, S. M., Rajasegarar, S., Karunasekera, S., and Leckie, C · 2016
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Goodfellow, I., Bengio, Y., and Courville, A · 2016
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Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
Schlegl, T., Seeböck, P., Waldstein, S. M., Schmidt-Erfurth, U., and Langs, G · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Zhu, J.-Y., Park, T., Isola, P., and Efros, A. A · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K · 2018
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Adversarially learned anomaly detection
Houssam Zenati, Manon Romain, C. S. F. B. L. V. R. C · 2018
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Memorization precedes generation: Learning unsupervised gans with memory networks
Kim, Y., Kim, M., and Kim, G · 2018
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Meta-learning with memory-augmented neural networks
Santoro, A., Bartunov, S., Botvinick, M., Wierstra, D., and Lillicrap, T
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Generative probabilistic novelty detection with adversarial autoencoders
Pidhorskyi, S., Almohsen, R., and Doretto, G · 2018
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Deep one-class classification
Ruff, L., Görnitz, N., Deecke, L., Siddiqui, S. A., Vandermeulen, R., Binder, A., Müller, E., and Kloft, M · 2018
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Deep autoencoding gaussian mixture model for unsupervised anomaly detection
Zong, B., Song, Q., Min, M. R., Cheng, W., Lumezanu, C., Cho, D., and Chen, H · 2018
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Gong, D., Liu, L., Le, V., Saha, B., Mansour, M. R., Venkatesh, S., and Hengel, A. v. d · 2019
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Anomaly detection with multiple-hypotheses predictions
Nguyen, D. T., Lou, Z., Klar, M., and Brox, T · 2019
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Regularized cycle consistent generative adversarial network for anomaly detection
Yang, Z., Soltani Bozchalooi, I., and Darve, E · 2020
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