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Applications in quantitative finance such as optimal trade execution, risk management of options, and optimal asset allocation involve the solution of high dimensional and nonlinear Partial Differential Equations (PDEs).
Stability and generalization
Olivier Bousquet and André Elisseeff · 2002
Earlier work this paper cites.
Stochastic calculus for finance II: Continuous-time models , volume 11
Steven E Shreve · 2004
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Multilevel monte carlo path simulation
Michael B Giles · 2008
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Arbitrage theory in continuous time
Tomas Björk · 2009
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Nonlinear option pricing
Julien Guyon and Pierre Henry-Labordere · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Algorithmic and high-frequency trading
Álvaro Cartea, Sebastian Jaimungal, and José Penalva · 2015
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Monte-Carlo methods and stochastic processes: from linear to non-linear
Emmanuel Gobet · 2016
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Deep residual learning for image recognition
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Transferability in machine learning: from phenomena to black-box attacks using adversarial samples
Nicolas Papernot, Patrick D. McDaniel, and Ian J. Goodfellow · 2016
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Eldad Haber and Lars Ruthotto · 2017
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Qianxiao Li, Long Chen, Cheng Tai, and E Weinan · 2017
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Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
Nais-net: stable deep networks from non-autonomous differential equations
Marco Ciccone, Marco Gallieri, Jonathan Masci, Christian Osendorfer, and Faustino Gomez · 2018
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Adversarial vulnerability for any classifier
Alhussein Fawzi, Hamza Fawzi, and Omar Fawzi · 2018
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Solving high-dimensional partial differential equations using deep learning
Jiequn Han, Arnulf Jentzen, and E Weinan · 2018
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Maziar Raissi · 2018
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Adversarial examples-a complete characterisation of the phenomenon
Alexandru Constantin Serban and Erik Poll · 2018
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Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
E Weinan, Jiequn Han, and Arnulf Jentzen · 2017
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Neural ordinary differential equations
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Deep learning as optimal control problems: models and numerical methods
Martin Benning, Elena Celledoni, Matthias J Ehrhardt, Brynjulf Owren, and Carola-Bibiane Schönlieb · 2019
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Eldad Haber, Keegan Lensink, Eran Triester, and Lars Ruthotto · 2019
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Deep learning theory review: An optimal control and dynamical systems perspective
Guan-Horng Liu and Evangelos A Theodorou · 2019
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