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The vector field of a controlled differential equation (CDE) describes the relationship between a control path and the evolution of a solution path.
An inequality of the hölder type, connected with stieltjes integration
Young, L. C · 1936
Earlier work this paper cites.
A basis for free lie rings and higher commutators in free groups
Hall, M · 1950
Earlier work this paper cites.
Integration of paths, geometric invariants and a generalized baker- hausdorff formula
Chen, K. T · 1957
Earlier work this paper cites.
Lie elements and an algebra associated with shuffles
Ree, R · 1958
Earlier work this paper cites.
Singular Integrals and Differentiability Properties of Functions (PMS-30)
Stein, E. M · 1970
Earlier work this paper cites.
Learning translation invariant recognition in massively parallel networks
Hinton, G. E · 1987
Earlier work this paper cites.
A simple weight decay can improve generalization
Krogh, A. and Hertz, J. A · 1991
Earlier work this paper cites.
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Reutenauer, C · 1993
Earlier work this paper cites.
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Lyons, T · 1994
Earlier work this paper cites.
Differential equations driven by rough signals
Lyons, T. J · 1998
Earlier work this paper cites.
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Earlier work this paper cites.
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Lyons, T., Caruana, M., and Lévy, T · 2007
Earlier work this paper cites.
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Roman, S · 2007
Earlier work this paper cites.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Efficiently modeling long sequences with structured state spaces
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