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Machine learning, and in particular neural network models, have revolutionized fields such as image, text, and speech recognition.
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Large portfolio losses: A dynamic contagion model
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Heterogeneous credit portfolios and the dynamics of the aggregate losses
P. Dai Pra and M. Tolotti · 2009
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Nonlinear Markov processes and kinetic equations
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Default clustering in large portfolios: Typical events
K. Giesecke, K. Spiliopoulos, and R. Sowers · 2013
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Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. Le · 2014
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Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, L. Wolf · 2014
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Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning
B. Alipanahi, A. Delong, M. Weirauch, and B. Frey · 2015
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Systemic risk in interbanking networks
L. Bo and A. Capponi · 2015
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Particle systems with a singular mean-field self-excitation. Application to neuronal networks
F. Delarue, J. Inglis, S. Rubenthaler, and E. Tanre · 2015
Deep voice: Real-time neural text-to-speech
S. Arik, M. Chrzanowski, A. Coates, G. Diamos, A. Gibiansky, Y. Kang, X. Li, J. Miller, A. Ng, J. Raiman, S. Sengputa · 2017
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Spectrally-normalized margin bounds for neural networks
P. Bartlett, D. Foster, and M. Telgarsky · 2017
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Improving Multi-Document Summarization via Text Classification
Z. Cao, W. Li, S. Li, and F. Wei · 2017
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Dermatologist-level classification of skin cancer with deep neural networks
A. Esteva, B. Kuprel, R. Novoa, J. Ko, S. Swetter, H. Blau, and S. Thrun · 2017
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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
S. Gu, E. Holly, T. Lillicrap, and S. Levine · 2017
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Large portfolio asymptotics for loss from default
K. Giesecke, K. Spiliopoulos, R. Sowers, and J. Sirignano · 2015
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Mean-field limit of a stochastic particle system smoothly interacting through threshold hitting-times and applications to neural networks with dendritic component
J. Inglis and D. Talay · 2015
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Deep Learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
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End to end learning for self-driving cars,
M. Bojarski, D. Del Test, D. Dworakowski, B. Firnier, B. Flepp, P. Goyal, L. Jackel, M. Monfort, U. Muller, J. Zhang, and X. Zhang · 2016
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Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
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Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
J. Ling, A. Kurzawski, and J. Templeton · 2016
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A stochastic McKean-Vlasov equation for absorbing diffusions on the half-line
B. Hambly and S. Ledger · 2017
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Deep learning in robotics: a review of recent research
H. Pierson and M. Gashler · 2017
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C. Wang, J. Mattingly, and Y. Lu · 2017
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Very deep convolutional networks for end-to-end speech recognition
Y. Zhang, W. Chan, and N. Jaitly · 2017
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On the global convergence of gradient descent for over-parameterized models using optimal transport
L. Chizat, and F. Bach · 2018
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Google Duplex: An AI System for Accomplishing Real-World Tasks Over the Phone
Y. Leviathan and Y. Matias · 2018
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A mean field view of the landscape of two-layer neural networks
S. Mei, A. Montanari, and P. Nguyen · 2018
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G. M. Rotskoff and E. Vanden-Eijnden · 2018
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Universal features of price formation in financial markets: perspectives from Deep Learning
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DGM: A deep learning algorithm for solving partial differential equations
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The limits and potentials of deep learning for robotics
N. Sunderhauf, O. Brock, W. Cheirer, R. Hadsell, D. Fox, J. Leitner, B. Upcroft, P. Abbeel, W. Burgard, M. Milford, and P. Corke · 2018
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Mean field analysis of neural networks: A central limit theorem
J. Sirignano and K. Spiliopoulos · 2019
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Mean field analysis of deep neural networks
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