Neural Processes

Add to your list(s) Download to your calendar using vCal

• Andrew Foong, Stratis Markou and Sebastian Ober (University of Cambridge)
• Wednesday 02 December 2020, 11:00-12:30
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09.

If you have a question about this talk, please contact Elre Oldewage.

Neural Processes (NPs) are a recently proposed method for using meta-learning to train neural networks to predict stochastic processes. They can be applied in regression tasks that require prediction with uncertainty in the small-data regime and fast test-time inference. Furthermore, the meta-learning framework allows NPs to learn intricate structure in the stochastic process directly from the data, allowing them to be applied to image data. In this reading group, we will introduce the basic NP architecture and go through some of the many kinds of NP that have been proposed since 2018, including the attentive NP and convolutional NP.

Suggested reading:

The talk will largely follow the content of this blog, which also includes code/pre-trained models: https://yanndubs.github.io/Neural-Process-Family

Conditional Neural Processes: https://arxiv.org/abs/1807.01613

Neural Processes: https://arxiv.org/abs/1807.01622

This talk is part of the Machine Learning Reading Group @ CUED series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge University Engineering Department Talks
• Cambridge talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Computational Continuum Mechanics Group Seminars
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Journal Clubs
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• ML
• Machine Learning Reading Group
• Machine Learning Reading Group @ CUED
• Machine Learning Summary
• Quantum Matter Journal Club
• Required lists for MLG
• School of Technology
• Simon Baker's List
• TQS Journal Clubs
• Trust & Technology Initiative - interesting events
• bld31
• custom
• https://eng-cam.zoom.us/j/86068703738?pwd=YnFleXFQOE1qR1h6Vmtwbno0LzFHdz09
• ndk22's list
• ob366-ai4er
• rp587
• yk373's list
• yk449

Note that ex-directory lists are not shown.