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Anomaly Detection on Financial Time Series by Principal Component
  Analysis and Neural Networks
v1v2 (latest)

Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural Networks

22 September 2022
Stéphane Crépey Lpsm
Lehdili Noureddine
Nisrine Madhar Lpsm
Maud Thomas Lpsm
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural Networks"

17 / 17 papers shown
Title
Applications of Signature Methods to Market Anomaly Detection
Applications of Signature Methods to Market Anomaly Detection
Erdinç Akyıldırım
Matteo Gambara
Josef Teichmann
Syang Zhou
129
21
0
07 Jan 2022
Anomaly Detection in Univariate Time-series: A Survey on the
  State-of-the-Art
Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art
Mohammad Braei
Sebastian Wagner
AI4TS
36
194
0
01 Apr 2020
Time Series Data Augmentation for Deep Learning: A Survey
Time Series Data Augmentation for Deep Learning: A Survey
Qingsong Wen
Liang Sun
Fan Yang
Xiaomin Song
Jing Gao
Xue Wang
Huan Xu
AI4TS
73
644
0
27 Feb 2020
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and
  Convolutional Neural Networks
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
Jing Gao
Xiaomin Song
Qingsong Wen
Pichao Wang
Liang Sun
Huan Xu
AI4TS
57
134
0
21 Feb 2020
XGBOD: Improving Supervised Outlier Detection with Unsupervised
  Representation Learning
XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning
Yue Zhao
Maciej K. Hryniewicki
72
121
0
01 Dec 2019
ROCKET: Exceptionally fast and accurate time series classification using
  random convolutional kernels
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
Angus Dempster
Franccois Petitjean
Geoffrey I. Webb
AI4TS
78
780
0
29 Oct 2019
Faster Algorithms for High-Dimensional Robust Covariance Estimation
Faster Algorithms for High-Dimensional Robust Covariance Estimation
Yu Cheng
Ilias Diakonikolas
Rong Ge
David P. Woodruff
59
66
0
11 Jun 2019
Deep Semi-Supervised Anomaly Detection
Deep Semi-Supervised Anomaly Detection
Lukas Ruff
Robert A. Vandermeulen
Nico Görnitz
Alexander Binder
Emmanuel Müller
K. Müller
Marius Kloft
UQCV
58
547
0
06 Jun 2019
Extended Isolation Forest
Extended Isolation Forest
Li Tang
Konstantinos Konstantinidis
R. Brunner
150
290
0
06 Nov 2018
Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings
Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings
Mehmet Necip Kurt
Y. Yilmaz
Xiaodong Wang
AI4TS
49
52
0
14 Sep 2018
Limiting the Reconstruction Capability of Generative Neural Network
  using Negative Learning
Limiting the Reconstruction Capability of Generative Neural Network using Negative Learning
Asim Munawar
Phongtharin Vinayavekhin
Giovanni De Magistris
48
47
0
16 Aug 2017
Real-valued (Medical) Time Series Generation with Recurrent Conditional
  GANs
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
Cristóbal Esteban
Stephanie L. Hyland
Gunnar Rätsch
GANSyDaMedIm
112
791
0
08 Jun 2017
Data Augmentation of Wearable Sensor Data for Parkinson's Disease
  Monitoring using Convolutional Neural Networks
Data Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks
T. T. Um
Franz MJ Pfister
Daniel C. Pichler
Satoshi Endo
Muriel Lang
Sandra Hirche
U. Fietzek
Dana Kulić
90
681
0
02 Jun 2017
Statistical Anomaly Detection via Composite Hypothesis Testing for
  Markov Models
Statistical Anomaly Detection via Composite Hypothesis Testing for Markov Models
Jing Zhang
I. Paschalidis
26
24
0
27 Feb 2017
Multi-Scale Convolutional Neural Networks for Time Series Classification
Multi-Scale Convolutional Neural Networks for Time Series Classification
Zhicheng Cui
Wenlin Chen
Yixin Chen
47
566
0
22 Mar 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,364
0
22 Dec 2014
Toward Supervised Anomaly Detection
Toward Supervised Anomaly Detection
Nico Görnitz
Marius Kloft
Konrad Rieck
Ulf Brefeld
AAML
75
387
0
23 Jan 2014
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