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Training deep learning models that generalize well to live deployment is a challenging problem in the financial markets.
Stock market prices do not follow random walks: Evidence from a simple specification test
Andrew W Lo and A Craig MacKinlay · 1988
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Using dynamic time warping to find patterns in time series
Donald J Berndt and James Clifford · 1994
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Object recognition with gradient-based learning
Yann LeCun, Patrick Haffner, Léon Bottou, and Yoshua Bengio · 1999
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Technical analysis of the financial markets: A comprehensive guide to trading methods and applications
John J Murphy · 1999
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The curse of dimensionality in data mining and time series prediction
Michel Verleysen and Damien François · 2005
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Toward accurate dynamic time warping in linear time and space
Stan Salvador and Philip Chan · 2007
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
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Principal component analysis
Ian Jolliffe · 2011
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Generalized denoising auto-encoders as generative models
Yoshua Bengio, Li Yao, Guillaume Alain, and Pascal Vincent · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2015
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Latent constraints: Learning to generate conditionally from unconditional generative models
Jesse Engel, Matthew Hoffman, and Adam Roberts · 2017
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The effectiveness of data augmentation in image classification using deep learning
Luis Perez and Jason Wang · 2017
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Veegan: Reducing mode collapse in gans using implicit variational learning
Akash Srivastava, Lazar Valkov, Chris Russell, Michael U Gutmann, and Charles Sutton · 2017
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Data augmentation using synthetic data for time series classification with deep residual networks
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, and Pierre-Alain Muller · 2018
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Martin Arjovsky and Léon Bottou · 2017
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Thomas Fischer and Christopher Krauss · 2018
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Generating virtual scenarios of multivariate financial data for quantitative trading applications
Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Jorge Cubero, Maria Planas, Rafael Cobo, and Fernando Pablos · 2018
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Use of hypothetical data in machine learning trading strategies
QPLUM LLC · 2018
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