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UID:2523@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20181019T140000
DTEND;TZID=Europe/Paris:20181019T150000
DTSTAMP:20181004T120000Z
URL:https://www.i2m.univ-amu.fr/evenements/time-series-generation-with-sca
 ttering-inverse-networks/
SUMMARY: (...): Time-series generation with scattering inverse networks
DESCRIPTION:: We introduce a Scattering Inverse Network (SIN) to generate u
 nivariate time-series.The SIN is similar to a deep convolutional autoencod
 er. However\, the encoder is not learned\, but computed with a scattering 
 transform defined from prior information on sparse time-frequency properti
 es of time-series. In turn\, the generator is trained by solving an invers
 e problem in an adapted metric. It has a similar causal architecture as a 
 WaveNet and provides a simpler mathematical model related to time-frequenc
 y decompositions.Numerical experiments demonstrate that this SIN generates
  realistic musical and speech signals. It is able to transform low-level m
 usical attributes such as pitch with a linear transformation in the embedd
 ing space of scattering coefficients. http://www.di.ens.fr/~andreux/
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