Gaussian Processes and Infinitely Wide Neural Networks

London Data Science Journal Club
London Data Science Journal Club
Public group
Location image of event venue


** we are meeting at a new venue this month, kindly sponsored by G-Research **

- 18:30: Doors open, pizza, drinks, networking
- 19:00: Meet up starts with an introduction to the topic
- 19:20: Discuss papers in groups
- 21:00: Close

In recent years there has been a flurry of activity detailing the link
between Gaussian Processes and infinitely wide neural networks.

Notable papers are:
1) Deep neural networks as Gaussian processes, Lee et al 2018,
with code at

2) Neural Tangent Kernel, Jacot et al, 2018,
with an implementation at

In this journal club we wish to explore this connection by discussing
the two articles above. The following prior work can help as an
introduction to the field:

Priors for infinite networks, Neal 1994,

Computing with infinite networks, Williams 1996,

A note about the Journal Club format:

1. The sessions usually start with a 5-10 minute introduction to the paper by the topic volunteer, followed by splitting into smaller groups to discuss the paper and other materials. We finish the session by coming together for about 15 minutes to discuss what we have learned as a group and ask questions around the room.
2. There is no speaker at Journal Club. One of the community has volunteered their time to suggest the topic and start the session, but most of the discussion comes from within the groups.
3. You will get more benefit from the session if you read the paper or other materials in advance. We try to provide (where we can find them) accompanying blog posts, relevant code and other summaries of the topic to serve as entry points.
4. If you don't have time to do much preparation, please come anyway. You will probably have something to contribute, and even if you just end up following the other discussions, you can still learn a lot.
5. It's OK just to read the blog post or watch the video :)
6. We don't have spare copies of the paper during the session, so please print out your own if you want a hard copy for discussion. For digital copies, you are welcome to use your laptops/tablets/phones during the session.