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SUMMARY:Advances in Neural Processes - Prof. Richard Turner.
DTSTART:20210929T130000Z
DTEND:20210929T140000Z
UID:TALK161965@talks.cam.ac.uk
CONTACT:102376
DESCRIPTION:The Cambridge ELLIS Unit has started a Seminar Series that wil
 l include talks by leading researchers in the area of machine learning and
  AI. Our next speaker will be Prof. Richard Turner. Details of his talk c
 an be found below. \n\nTitle: “Advances in Neural Processes”\n\nAbstra
 ct: Traditional deep learning algorithms fit their parameters to a dataset
  using an iterative method like gradient descent and return predictions at
  a set of user-specified locations. Taken together\, a deep learning algor
 ithm can be viewed as a function -- albeit a complex one -- that takes the
  dataset as input\, computes model parameters\, and returns predictions. I
 n a neural process\, this mapping from datasets to predictive distribution
 s is modelled directly instead. In this way\, neural processes blend ideas
  from deep learning\, with those of stochastic processes like the famous G
 aussian Process. They also connect to meta-learning approaches as they are
  trained by considering a set of tasks. Neural processes have a host of pr
 omising applications for example to irregularly sampled time-series that a
 re encountered in healthcare settings and off-the-grid spatial data which 
 is encountered in environmental science. There has been a huge amount of r
 ecent activity in this area. My talk will give a short tutorial on neural 
 processes and explain some of the recent contributions my group has made t
 o this research effort.
LOCATION:https://eng-cam.zoom.us/j/85186218549?pwd=dDh0cGRua2FHdVp0U05rOVR
 UalJFUT09
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