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DTSTAMP:20201015T183000Z
UID:1602682701118@events.msu.edu
CATEGORIES:Conferences / Seminars / Lectures
DTSTART:20201015T183000Z
DTEND:20201015T193000Z
SUMMARY:Math Seminar Series
DESCRIPTION:
Applied Mathematics\n
\n
Reinhard Heckel from the
Technical University of Munich will be speaking.\n
\n
The
presentation is titled "Provable
Image Recovery with Untrained Convolutional
Neural Networks."\n
\n
This is a virtual meeting.\n
\n
Contact
Olga Turanova (turanova@msu.edu)
for more information.\n
\n
The abstract is as
follows:\n
\n
Convolutional Neural Networks are
highly successful tools for image recovery
and restoration. A major contributing factor
to this success is that convolutional networks
impose strong prior assumptions about natural
images-so strong that they enable image recovery
without any training data. A surprising
observation that highlights those prior assumptions
is that one can remove noise from a
corrupted natural image by simply fitting (via
gradient descent) a randomly initialized, over-parameterized
convolutional generator to
the noisy image. In this talk, we discuss a simple
un-trained convolutional network, called
the deep decoder, that provably enables image
denoising and regularization of inverse problems
such as compressive sensing with excellent
performance. We formally characterize the
dynamics of fitting this convolutional network
to a noisy signal and to an under-sampled
signal, and show that in both cases early-stopped
gradient descent provably recovers the
clean signal. Finally, we discuss our own numerical
results and numerical results from another
group demonstrating that un-trained convolutional
networks enable magnetic resonance
imaging from highly under-sampled measurements,
achieving results surprisingly close to trained
networks, and outperforming classical untrained
methods.\n\n
Price: free\n
Sponsor: Department of Mathematics\n
Sponsor's Homepage: https://www.math.msu.edu/\n
Contact name: Department of Mathematics\n
Contact phone: (517) 353-0844\n
for more info visit the web at:\n
https://www.math.msu.edu/Seminars/CalendarView.aspx?month-of=September2016\n
LOCATION:Zoom link provided on Math Seminars page
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